Systems and methods are disclosed for determining anatomy directly from raw medical acquisitions using a machine learning system. One method includes obtaining raw medical acquisition data from transmission and collection of energy and particles traveling through and originating from bodies of one or more individuals; obtaining a parameterized model associated with anatomy of each of the one or more individuals; determining one or more parameters for the parameterized model, wherein the parameters are associated with the raw medical acquisition data; training a machine learning system to predict one or more values for each of the determined parameters of the parametrized model, based on the raw medical acquisition data; acquiring a medical acquisition for a selected patient; and using the trained machine learning system to determine a parameter value for a patient-specific parameterized model of the patient.
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
2.
METHOD AND SYSTEM FOR PROVIDING INFORMATION FROM A PATIENT-SPECIFIC MODEL OF BLOOD FLOW
Embodiments include a system for providing blood flow information for a patient. The system may include at least one computer system including a touchscreen. The at least one computer system may be configured to display, on the touchscreen, a three-dimensional model representing at least a portion of an anatomical structure of the patient based on patient-specific data. The at least one computer system may also be configured to receive a first input relating to a first location on the touchscreen indicated by at least one pointing object controlled by a user, and the first location on the touchscreen may indicate a first location on the displayed three-dimensional model. The at least one computer system may be further configured to display first information on the touchscreen, and the first information may indicate a blood flow characteristic at the first location.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G06F 30/20 - Design optimisation, verification or simulation
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G06F 3/04815 - Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
G06T 15/00 - 3D [Three Dimensional] image rendering
A61B 5/021 - Measuring pressure in heart or blood vessels
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
Systems and methods are disclosed for identifying image acquisition parameters. One method includes receiving a patient data set including one or more reconstructions, one or more preliminary scans or patient information, and one or more acquisition parameters; computing one or more patient characteristics based on one or both of one or more preliminary scans and the patient information; computing one or more image characteristics associated with the one or more reconstructions; grouping the patient data set with one or more other patient data sets using the one or more patient characteristics; and identifying one or more image acquisition parameters suitable for the patient data set using the one or more image characteristics, the grouping of the patient data set with one or more other patient data sets, or a combination thereof.
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
5.
Systems and methods for identifying personalized vascular implants from patient-specific anatomic data
Embodiments include methods of identifying a personalized cardiovascular device based on patient-specific geometrical information, the method comprising acquiring a geometric model of at least a portion of a patient's vascular system; obtaining one or more geometric quantities of one or more blood vessels of the geometric model of the patient's vascular system; determining the presence or absence of a pathology characteristic at a location in the geometric model of the patient's vascular system; generating an objective function defined by a plurality of device variables and a plurality of hemodynamic and solid mechanics characteristics; and optimizing the objective function using computational fluid dynamics and structural mechanics analysis to identify a plurality of device variables that result in desired hemodynamic and solid mechanics characteristics.
Systems and methods are disclosed for assessing the quality of medical images of at least a portion of a patient's anatomy, using a computer system. One method includes receiving one or more images of at least a portion of the patient's anatomy; determining, using a processor of the computer system, one or more image properties of the received images; performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images; obtaining an identification of one or more image characteristics associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and calculating, using a processor of the computer system, an image quality score based on the one or more image properties and the one or more image characteristics.
Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/0215 - Measuring pressure in heart or blood vessels by means inserted into the body
8.
METHODS AND SYSTEMS FOR PREDICTING SENSITIVITY OF BLOOD FLOW CALCULATIONS TO CHANGES IN ANATOMICAL GEOMETRY
Embodiments include methods and systems and for determining a sensitivity of a patient's blood flow characteristic to anatomical or geometrical uncertainty. For each of one or more of individuals, a sensitivity of a blood flow characteristic may be obtained for one or more uncertain parameters. An algorithm may be trained based on the sensitivities of the blood flow characteristic and one or more of the uncertain parameters for each of the plurality of individuals. A geometric model, a blood flow characteristic, and one or more of the uncertain parameters of at least part of the patient's vascular system may be obtained for a patient. The sensitivity of the patient's blood flow characteristic to one or more of the uncertain parameters may be calculated by executing the algorithm on the blood flow characteristic of at least part of the patient's vascular system, and one or more of the uncertain parameters.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
Systems and methods are disclosed for controlling image annotation. One method includes acquiring a digital representation of image data and generating a set of image annotations for the digital representation of the image data. The method also may include determining an association between members of the set of image annotations and generating one or more groups of members based on the association. A representative annotation from the one or more groups may also be determined, presented for selection, and the selection may be recorded in memory.
G06F 3/04842 - Selection of displayed objects or displayed text elements
G06F 3/04845 - Interaction techniques based on graphical user interfaces [GUI] for the control of specific functions or operations, e.g. selecting or manipulating an object, an image or a displayed text element, setting a parameter value or selecting a range for image manipulation, e.g. dragging, rotation, expansion or change of colour
G06T 11/60 - Editing figures and text; Combining figures or text
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
10.
SYSTEM AND METHOD FOR PROCESSING ELECTRONIC IMAGES FOR VASCULAR TREE GENERATION
Systems and methods are disclosed for simulating microvascular networks from a vascular tree model to simulate tissue perfusion under various physiological conditions to guide diagnosis or treatment for cardiovascular disease. One method includes: receiving a patient-specific vascular model of a patient's anatomy, including a vascular network; receiving a patient-specific target tissue model in which a blood supply may be estimated; receiving joint prior information associated with the vascular model and the target tissue model; receiving data related to one or more perfusion characteristics of the target tissue; determining one or more associations between the vascular network of the patient-specific vascular model and one or more perfusion characteristics of the target tissue using the joint prior information; and outputting a vascular tree model that extends to perfusion regions in the target tissue, using the determined associations between the vascular network and the perfusion characteristics.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
Systems and methods are disclosed for blood flow simulation. For example, a method may include performing a plurality of blood flow simulations using a first model of vascular blood flow, each of the plurality of blood flow simulations simulating blood flow in a vasculature of a patient or a geometry based on the vasculature of the patient; based on results of the plurality of blood flow simulations, generating a response surface mapping one or more first parameters of the first model to one or more second parameters of a reduced order model of vascular blood; determining values for the one or more parameters of the reduced order model mapped, by the response surface, from parameter values representing a modified state of the vasculature; and performing simulation using the reduced order model parameterized by the determined values, to determine a blood flow characteristic of the modified state of the vasculature.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
12.
SYSTEMS AND METHODS FOR PREDICTING CORONARY PLAQUE VULNERABILITY FROM PATIENT SPECIFIC ANATOMIC IMAGE DATA
Systems and methods are disclosed for predicting coronary plaque vulnerability, using a computer system. One method includes acquiring anatomical image data of at least part of the patient's vascular system; performing, using a processor, one or more image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis on the anatomical image data; predicting, using the processor, a coronary plaque vulnerability present in the patient's vascular system, wherein predicting the coronary plaque vulnerability includes calculating an adverse plaque characteristic based on results of the one or more of image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis of the anatomical image data; and reporting, using the processor, the calculated adverse plaque characteristic.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
Systems and methods are disclosed for correcting for artificial deformations in anatomical modeling. One method includes obtaining an anatomic model; obtaining information indicating a presence of an artificial deformation of the anatomic model; identifying a portion of the anatomic model associated with the artificial deformation; estimating a non-deformed local area corresponding to the portion of the anatomic model; and modifying the portion of the anatomic model associated with the artificial deformation, based on the estimated non-deformed local area.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G06F 30/20 - Design optimisation, verification or simulation
G06F 18/22 - Matching criteria, e.g. proximity measures
Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
15.
SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES TO PREDICT LESIONS
Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
16.
Systems and methods for identifying and modeling unresolved vessels in image-based patient-specific hemodynamic models
Systems and methods are disclosed for identifying and modeling unresolved vessels, and the effects thereof, in image-based patient-specific hemodynamic models. One method includes: receiving, in an electronic storage medium, one or more patient-specific anatomical models representing at least a vessel of a patient; determining, using a processor, the values and characteristics of one or more patient-specific morphometric features in the one or more patient-specific anatomical models; modifying the patient-specific anatomical model using the determined patient-specific morphometric features; and outputting, one or more of, a modified patient-specific anatomical model or a patient-specific morphometric feature to an electronic storage medium or display.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
17.
SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES TO ASSESS END-ORGAN DEMAND
Systems and methods are disclosed for to determining a blood supply and blood demand. One method includes receiving a patient-specific model of vessel geometry of at least a portion of a coronary artery, wherein the model is based on patient-specific image data of at least a portion of a patient's heart having myocardium; determining a coronary blood supply based on the patient-specific model; determining at least a portion of the myocardium corresponding to the coronary artery; determining a myocardial blood demand based on either a mass or a volume of the portion of the myocardium, or based on perfusion imaging of the portion of the myocardium; and determining a relationship between the coronary blood supply and the myocardial blood demand.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Systems and methods are disclosed for determining blood flow characteristics of a patient. One method includes: receiving, in an electronic storage medium, patient-specific image data of at least a portion of vasculature of the patient having geometric features at one or more points; generating a patient-specific reduced order model from the received image data, the patient-specific reduced order model comprising estimates of impedance values and a simplification of the geometric features at the one or more points of the vasculature of the patient; creating a feature vector comprising the estimates of impedance values and geometric features for each of the one or more points of the patient-specific reduced order model; and determining blood flow characteristics at the one or more points of the patient-specific reduced order model using a machine learning algorithm trained to predict blood flow characteristics based on the created feature vectors at the one or more points.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
19.
SYSTEMS AND METHODS FOR AN INTERACTIVE TOOL FOR DETERMINING AND VISUALIZING A FUNCTIONAL RELATIONSHIP BETWEEN A VASCULAR NETWORK AND PERFUSED TISSUE
Systems and methods are disclosed for creating an interactive tool for determining and displaying a functional relationship between a vascular network and an associated perfused tissue. One method includes receiving a patient-specific vascular model of a patient’s anatomy, including at least one vessel of the patient; receiving a patient-specific tissue model, including a tissue region associated with the at least one vessel of the patient; receiving a selected area of the vascular model or a selected area of the tissue model; and generating a display of a region of the tissue model corresponding to the selected area of the vascular model or a display of a portion of the vascular model corresponding to the selected area of the tissue model, respectively.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 34/00 - Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
20.
SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES TO IDENTIFY RELEVANT FLOW CHARACTERISTICS
Systems and methods are disclosed for identifying anatomically relevant blood flow characteristics in a patient. One method includes: receiving, in an electronic storage medium, a patient-specific representation of at least a portion of vasculature of the patient having a lesion at one or more points; receiving values for one or more metrics of interest associated with one or more locations in the vasculature of the patient; receiving one or more observed lumen measurements of the vasculature of the patient; determining the location of a diseased region in the vasculature of the patient using the received values for the one or more metrics of interest, wherein the determination of the location includes predicting or receiving one or more healthy lumen measurements of the vasculature of the patient; determining the extent of the diseased region; and generating a visualization of at least the diseased region.
A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 90/00 - Instruments, implements or accessories specially adapted for surgery or diagnosis and not covered by any of the groups , e.g. for luxation treatment or for protecting wound edges
A61B 5/021 - Measuring pressure in heart or blood vessels
21.
SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES TO SIMULATE FLOW
Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
A61M 5/00 - Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm rests
G06T 7/70 - Determining position or orientation of objects or cameras
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
G06F 30/20 - Design optimisation, verification or simulation
G16H 70/00 - ICT specially adapted for the handling or processing of medical references
A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
A61B 5/029 - Measuring blood output from the heart, e.g. minute volume
A61B 5/021 - Measuring pressure in heart or blood vessels
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
A61B 5/22 - Ergometry; Measuring muscular strength or the force of a muscular blow
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G06T 7/149 - Segmentation; Edge detection involving deformable models, e.g. active contour models
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
A61B 5/107 - Measuring physical dimensions, e.g. size of the entire body or parts thereof
A61B 90/00 - Instruments, implements or accessories specially adapted for surgery or diagnosis and not covered by any of the groups , e.g. for luxation treatment or for protecting wound edges
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
22.
Systems and methods for embolism prediction using embolus source and destination probabilities
Systems and methods are disclosed for determining a patient risk assessment or treatment plan based on emboli dislodgement and destination. One method includes receiving a patient-specific anatomic model generated from patient-specific imaging of at least a portion of a patient's vasculature; determining or receiving a location of interest in the patient-specific anatomic model of the patient's vasculature; using a computing processor for calculating blood flow through the patient-specific anatomic model to determine blood flow characteristics through at least the portion of the patient's vasculature of the patient-specific anatomic model downstream from the location of interest; and using a computing processor for particle tracking through the simulated blood flow to determine a destination probability of an embolus originating from the location of interest in the patient-specific anatomic model, based on the determined blood flow characteristics.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G06F 17/18 - Complex mathematical operations for evaluating statistical data
23.
Systems and methods for risk assessment and treatment planning of arterio-venous malformation
A computer implemented method for assessing an arterio-venous malformation (AVM) may include, for example, receiving a patient-specific model of a portion of an anatomy of a patient; using a computer processor to analyze the patient-specific model for identifying one or more blood vessels associated with the AVM, in the patient-specific model; and estimating a risk of an undesirable outcome caused by the AVM, by performing computer simulations of blood flow through the one or more blood vessels associated with the AVM in the patient-specific model.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
24.
SYSTEMS AND METHODS FOR ANATOMIC STRUCTURE SEGMENTATION IN IMAGE ANALYSIS
Systems and methods are disclosed for anatomic structure segmentation in image analysis, using a computer system. One method includes: receiving an annotation and a plurality of keypoints for an anatomic structure in one or more images; computing distances from the plurality of keypoints to a boundary of the anatomic structure; training a model, using data in the one or more images and the computed distances, for predicting a boundary in the anatomic structure in an image of a patient's anatomy; receiving the image of the patient's anatomy including the anatomic structure; estimating a segmentation boundary in the anatomic structure in the image of the patient's anatomy; and predicting, using the trained model, a boundary location in the anatomic structure in the image of the patient's anatomy by generating a regression of distances from keypoints in the anatomic structure in the image of the patient's anatomy to the estimated boundary.
Systems and methods are disclosed for assessing tissue function based on vascular disease. One method includes receiving a patient-specific anatomic model generated from patient-specific imaging of at least a portion of a patient's tissue; receiving a patient-specific vascular model generated from patient-specific imaging of at least a portion of a patient's vasculature; receiving an estimate of blood supplied to a portion of the patient-specific anatomic model; and determining a characteristic of the function of the patient's tissue using the estimate of blood supplied to the portion of the patient-specific anatomic model.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
26.
SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES USING USER INPUTS
A computer-implemented method for medical measurement reconstruction may comprise obtaining a first reconstruction of at least one representation of at least one set of medical measurements; presenting the first reconstruction or information about the first reconstruction to a reviewer; receiving an input from the reviewer relating to the first reconstruction or the information about the first reconstruction; processing the received input; and generating a second, modified reconstruction based on the received input.
A computer-implemented method for medical measurement reconstruction may comprise: receiving a measurement acquisition signal; based on the received measurement acquisition signal, creating a plurality of representations of the measurement acquisition signal, wherein each of the plurality of representations relates to a different aspect of the measurement acquisition signal; modifying one or more of the plurality of representations; and generating an output signal including the modified one or more of the plurality of representations.
A computer-implemented method for medical measurement reconstruction may comprise obtaining a first reconstruction of at least one representation of at least one set of medical measurements; presenting the first reconstruction or information about the first reconstruction to a reviewer; receiving an input from the reviewer relating to the first reconstruction or the information about the first reconstruction; processing the received input; and generating a second, modified reconstruction based on the received input.
A computer-implemented method for medical measurement reconstruction may comprise: receiving a measurement acquisition signal; based on the received measurement acquisition signal, creating a plurality of representations of the measurement acquisition signal, wherein each of the plurality of representations relates to a different aspect of the measurement acquisition signal; modifying one or more of the plurality of representations; and generating an output signal including the modified one or more of the plurality of representations.
Systems and methods are disclosed for providing a cardiovascular score for a patient. A method includes receiving, using at least one computer system, patient-specific data regarding a geometry of multiple coronary arteries of the patient; and creating, using at least one computer system, a three-dimensional model representing at least portions of the multiple coronary arteries based on the patient-specific data. The method also includes evaluating, using at least one computer system, multiple characteristics of at least some of the coronary arteries represented by the model; and generating, using at least one computer system, the cardiovascular score based on the evaluation of the multiple characteristics. Another method includes generating the cardiovascular score based on evaluated multiple characteristics for portions of the coronary arteries having fractional flow reserve values of at least a predetermined threshold value.
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
G06T 19/00 - Manipulating 3D models or images for computer graphics
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
31.
METHOD AND SYSTEM FOR QUANTIFYING LIMITATIONS IN CORONARY ARTERY BLOOD FLOW DURING PHYSICAL ACTIVITY IN PATIENTS WITH CORONARY ARTERY DISEASE
Embodiments include a system for determining cardiovascular information for a patient with coronary artery disease. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart and create a model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create, for a given level of physical activity, a physics-based model of blood flow through the patient's heart simulated during a selected level of physical activity; determine and normalize one or more values of at least one blood flow characteristic within the patient's heart during the simulated level of physical activity; and compare the one or more normalized values of the at least one blood flow characteristic to a threshold to determine whether the level of physical activity exceeds an acceptable level of risk.
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/029 - Measuring blood output from the heart, e.g. minute volume
A61B 5/021 - Measuring pressure in heart or blood vessels
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
32.
Method and system for image processing to model vasculasture
Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient's heart based on patient-specific data regarding a geometry of the patient's heart or vasculature; and for a plurality of treatment options for the patient's heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient's heart or vasculature, and one or more costs of each of the plurality of treatment options.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G06F 30/20 - Design optimisation, verification or simulation
G06V 40/20 - Movements or behaviour, e.g. gesture recognition
G06V 30/194 - References adjustable by an adaptive method, e.g. learning
G06V 10/40 - Extraction of image or video features
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
33.
SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES AND UPDATING BASED ON SENSOR DATA
Systems and methods are disclosed for informing and monitoring blood flow calculations with user-specific activity data, including sensor data. One method includes receiving or accessing a user-specific anatomical model and a first set of physiological characteristics of a user; calculating a first value of a blood flow metric of the user based on the user-specific anatomical model and the first set of physiological characteristics; receiving or calculating a second set of physiological characteristics of the user by accessing or receiving sensor data of the user's blood flow and/or sensor data of the user's physiological characteristics; and calculating second value of the blood flow metric of the user based on the user-specific anatomical model and the second set of physiological characteristics of the user.
G06F 16/00 - Information retrieval; Database structures therefor; File system structures therefor
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
Systems and methods are disclosed for integrating imaging data from multiple sources to create a single, accurate model of a patient's anatomy. One method includes receiving a representation of a target object for modeling; determining one or more first anatomical parameters of the target anatomical object from at least one of one or more first images of the target anatomical object; determining one or more second anatomical parameters of the target anatomical object from at least one of one or more second images of the target anatomical object; updating the one or more first anatomical parameters based at least on the one or more second anatomical parameters; and generating a model of the target anatomical object based on the updated first anatomical parameters.
Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/0215 - Measuring pressure in heart or blood vessels by means inserted into the body
36.
Systems and methods for assessing cardiovascular disease and treatment effectiveness from adipose tissue
Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
37.
SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES TO DETERMINE FLOW USING FLOW RATIO
Embodiments include a system for determining patient cardiovascular information which includes at least one computer system configured to receive patient-specific data regarding a geometry of an anatomical structure of a patient; create a model representing at least a portion of the anatomical structure of the patient based on the patient-specific data; determine a first blood flow rate at at least one point of interest in the model by using relations of individual-specific anatomic data to functional estimates of blood flow characteristics generated from a plurality of individuals; modify the model; determine a second blood flow rate at a point in the modified model corresponding to the at least one point of interest by using the relations of individual-specific anatomic data to functional estimates of blood flow characteristics; and determine a fractional flow reserve value as a ratio of the second blood flow rate to the first blood flow rate.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/021 - Measuring pressure in heart or blood vessels
G06T 19/00 - Manipulating 3D models or images for computer graphics
G06F 30/20 - Design optimisation, verification or simulation
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
A61B 5/029 - Measuring blood output from the heart, e.g. minute volume
A61B 5/107 - Measuring physical dimensions, e.g. size of the entire body or parts thereof
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
Systems and methods are disclosed for performing probabilistic segmentation in anatomical image analysis, using a computer system. One method includes receiving a plurality of images of an anatomical structure; receiving one or more geometric labels of the anatomical structure; generating a parametrized representation of the anatomical structure based on the one or more geometric labels and the received plurality of images; mapping a region of the parameterized representation to a geometric parameter of the anatomical structure; receiving an image of a patient's anatomy; and generating a probability distribution for a patient-specific segmentation boundary of the patient's anatomy, based on the mapping of the region of the parameterized representation of the anatomical structure to the geometric parameter of the anatomical structure.
Systems and methods are disclosed herein for anatomical modeling using information obtained during a medical procedure, whereby an initial anatomical model is generated or obtained, a correspondence is determined between the initial model and additional data and/or measurements from an invasive or noninvasive procedure, and, if a discrepancy is found between the initial model and the additional data, the anatomical model is updated to incorporate the additional data and reduce the discrepancy.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
40.
SYSTEMS AND METHODS FOR PROCESSING ELECTRONIC IMAGES TO DETERMINE A PLANAR MAPPING
A computer-implemented method for subject-specific two-dimensional modeling of a subject's vasculature may comprise: receiving a subject-specific three-dimensional model of the subject's vasculature, wherein the subject-specific three-dimensional model includes one or more centerlines; determining a two-dimensional viewing plane; determining a projection of the one or more centerlines of the subject-specific three-dimensional model onto the two-dimensional viewing plane; generating one or more models around the one or more centerlines; and generating a two-dimensional image depicting the one or more models.
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A computer-implemented method for subject-specific two-dimensional modeling of a subject's vasculature may comprise: receiving a subject-specific three-dimensional model of the subject's vasculature, wherein the subject-specific three-dimensional model includes one or more centerlines; determining a two-dimensional viewing plane; determining a projection of the one or more centerlines of the subject-specific three-dimensional model onto the two-dimensional viewing plane; generating one or more models around the one or more centerlines; and generating a two-dimensional image depicting the one or more models.
A computer-implemented method for subject-specific two-dimensional modeling of a subject's vasculature may comprise: receiving a subject-specific three-dimensional model of the subject's vasculature, wherein the subject-specific three-dimensional model includes one or more centerlines; determining a two-dimensional viewing plane; determining a projection of the one or more centerlines of the subject-specific three-dimensional model onto the two-dimensional viewing plane; generating one or more models around the one or more centerlines; and generating a two-dimensional image depicting the one or more models.
Systems and methods are disclosed for identifying and modeling unresolved vessels, and the effects thereof, in image-based patient-specific hemodynamic models. One method includes: receiving a patient-specific anatomical model of at least a portion of a visceral vascular system of the patient; receiving patient-specific information related to the patient's food intake; generating a patient-specific model of blood flow in the patient-specific anatomical model of the portion of the visceral vascular system of the patient; generating a patient-specific model of nutrient transport from at least a part of a gastrointestinal system of the patient to the portion of the visceral vascular system of the patient based on the patient-specific information related to the patient's food intake; and determining an indicia of energy available in the patient based on the patient-specific model of nutrient transport.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G09B 9/00 - Simulators for teaching or training purposes
44.
Systems and methods for medical acquisition processing and machine learning for anatomical assessment
Systems and methods are disclosed for determining anatomy directly from raw medical acquisitions using a machine learning system. One method includes obtaining raw medical acquisition data from transmission and collection of energy and particles traveling through and originating from bodies of one or more individuals; obtaining a parameterized model associated with anatomy of each of the one or more individuals; determining one or more parameters for the parameterized model, wherein the parameters are associated with the raw medical acquisition data; training a machine learning system to predict one or more values for each of the determined parameters of the parametrized model, based on the raw medical acquisition data; acquiring a medical acquisition for a selected patient; and using the trained machine learning system to determine a parameter value for a patient-specific parameterized model of the patient.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
A61B 5/021 - Measuring pressure in heart or blood vessels
A61B 5/107 - Measuring physical dimensions, e.g. size of the entire body or parts thereof
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
Systems and methods are disclosed for assessing the quality of medical images of at least a portion of a patient's anatomy, using a computer system. One method includes receiving one or more images of at least a portion of the patient's anatomy; determining, using a processor of the computer system, one or more image properties of the received images; performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images; obtaining an identification of one or more image characteristics associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and calculating, using a processor of the computer system, an image quality score based on the one or more image properties and the one or more image characteristics.
A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
G01R 33/563 - Image enhancement or correction, e.g. subtraction or averaging techniques of moving material, e.g. flow-contrast angiography
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
47.
SYSTEMS AND METHODS FOR ASSESSING THE SEVERITY OF PLAQUE AND/OR STENOTIC LESIONS USING CONTRAST DISTRIBUTION PREDICTIONS AND MEASUREMENTS
Systems and methods are disclosed for assessing the severity of plaque and/or stenotic lesions using contrast distribution predictions and measurements. One method includes: receiving patient-specific images of a patient's vasculature and a measured distribution of a contrast agent delivered through the patient's vasculature; associating the measured distribution of the contrast agent with a patient-specific anatomic model of the patient's vasculature; defining physiological and boundary conditions of a blood flow model of the patient's blood flow and pressure; simulating the distribution of the contrast agent through the patient-specific anatomic model; comparing the measured distribution of the contrast agent and the simulated distribution of the contrast agent through the patient-specific anatomic model to determine whether a similarity condition is satisfied; and updating the defined physiological and boundary conditions and re-simulating distribution of the contrast agent through the one or more points of the patient-specific anatomic model until the similarity condition is satisfied.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
48.
METHOD AND SYSTEM FOR IMAGE PROCESSING TO DETERMINE BLOOD FLOW
Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.
A61B 34/00 - Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
G06T 7/149 - Segmentation; Edge detection involving deformable models, e.g. active contour models
G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G06F 30/20 - Design optimisation, verification or simulation
G06F 30/23 - Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
G16H 70/00 - ICT specially adapted for the handling or processing of medical references
G06V 10/40 - Extraction of image or video features
G06V 10/42 - Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
A61M 5/00 - Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm rests
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
G06T 17/20 - Wire-frame description, e.g. polygonalisation or tessellation
G01R 33/56 - Image enhancement or correction, e.g. subtraction or averaging techniques
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
49.
Systems and methods for processing electronic images to predict lesions
Systems and methods are disclosed for predicting the location, onset, or change of coronary lesions from factors like vessel geometry, physiology, and hemodynamics. One method includes: acquiring, for each of a plurality of individuals, a geometric model, blood flow characteristics, and plaque information for part of the individual's vascular system; training a machine learning algorithm based on the geometric models and blood flow characteristics for each of the plurality of individuals, and features predictive of the presence of plaque within the geometric models and blood flow characteristics of the plurality of individuals; acquiring, for a patient, a geometric model and blood flow characteristics for part of the patient's vascular system; and executing the machine learning algorithm on the patient's geometric model and blood flow characteristics to determine, based on the predictive features, plaque information of the patient for at least one point in the patient's geometric model.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
G06N 7/01 - Probabilistic graphical models, e.g. probabilistic networks
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
50.
SYSTEMS AND METHODS FOR PROCESSING IMAGES TO DETERMINE PLAQUE PROGRESSION AND REGRESSION
Systems and methods are disclosed for evaluating a patient with vascular disease. One method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of a location of disease in the patient's vasculature based on the received patient-specific data; identifying one or more changes in geometry of the anatomic model based on a modeled progression or regression of disease at the location; calculating one or more values of a blood flow characteristic within the patient's vasculature using a computational model based on the identified one or more changes in geometry of the anatomic model; and generating an electronic graphical display of a relationship between the one or more values of the calculated blood flow characteristic and the identified one or more changes in geometry of the anatomic model.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
51.
Systems and methods for predicting image quality scores of images
Systems and methods are disclosed for identifying image acquisition parameters. One method includes receiving a patient data set including one or more reconstructions, one or more preliminary scans or patient information, and one or more acquisition parameters; computing one or more patient characteristics based on one or both of one or more preliminary scans and the patient information; computing one or more image characteristics associated with the one or more reconstructions; grouping the patient data set with one or more other patient data sets using the one or more patient characteristics; and identifying one or more image acquisition parameters suitable for the patient data set using the one or more image characteristics, the grouping of the patient data set with one or more other patient data sets, or a combination thereof.
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 40/63 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for local operation
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
52.
Method and system for image processing to determine blood flow
Systems and methods are disclosed for evaluating cardiovascular treatment options for a patient. One method includes creating a three-dimensional model representing a portion of the patient's heart based on patient-specific data regarding a geometry of the patient's heart or vasculature; and for a plurality of treatment options for the patient's heart or vasculature, modifying at least one of the three-dimensional model and a reduced order model based on the three-dimensional model. The method also includes determining, for each of the plurality of treatment options, a value of a blood flow characteristic, by solving at least one of the modified three-dimensional model and the modified reduced order model; and identifying one of the plurality of treatment options that solves a function of at least one of: the determined blood flow characteristics of the patient's heart or vasculature, and one or more costs of each of the plurality of treatment options.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G06F 30/20 - Design optimisation, verification or simulation
G06V 10/40 - Extraction of image or video features
G06V 30/194 - References adjustable by an adaptive method, e.g. learning
G06V 40/20 - Movements or behaviour, e.g. gesture recognition
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
53.
Systems and methods for risk assessment and treatment planning of arterio-venous malformation
A computer implemented method for assessing an arterio-venous malformation (AVM) may include, for example, receiving a patient-specific model of a portion of an anatomy of a patient; using a computer processor to analyze the patient-specific model for identifying one or more blood vessels associated with the AVM, in the patient-specific model; and estimating a risk of an undesirable outcome caused by the AVM, by performing computer simulations of blood flow through the one or more blood vessels associated with the AVM in the patient-specific model.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
54.
Systems and methods for correction of artificial deformation in anatomic modeling
Systems and methods are disclosed for correcting for artificial deformations in anatomical modeling. One method includes obtaining an anatomic model; obtaining information indicating a presence of an artificial deformation of the anatomic model; identifying a portion of the anatomic model associated with the artificial deformation; estimating a non-deformed local area corresponding to the portion of the anatomic model; and modifying the portion of the anatomic model associated with the artificial deformation, based on the estimated non-deformed local area.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G06F 30/20 - Design optimisation, verification or simulation
Systems and methods are disclosed for predicting healthy lumen radius and calculating a vessel lumen narrowing score. One method of identifying a lumen diameter of a patient's vasculature includes: receiving a data set including one or more lumen segmentations of known healthy vessel segments of a plurality of individuals; extracting one or more lumen features for each of the vessel segments; receiving a lumen segmentation of a patient's vasculature; determining a section of the patient's vasculature; and determining a healthy lumen diameter of the section of the patient's vasculature using the extracted one or more features for each of the known healthy vessel segments of the plurality of individuals.
G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
56.
Systems and methods for processing electronic images across regions
Systems and methods are disclosed for preserving patient privacy while transmitting health data from one geographic region to another geographic region for data analysis. One method includes receiving patient-specific health data including patient privacy information at a first region; removing the patient privacy information from the patient-specific health data to generate anonymous health data; storing the patient privacy information at the first region; and transmitting the anonymous health data to a second region for analysis.
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
57.
Systems and methods for anatomic structure segmentation in image analysis
Systems and methods are disclosed for anatomic structure segmentation in image analysis, using a computer system. One method includes: receiving an annotation and a plurality of keypoints for an anatomic structure in one or more images; computing distances from the plurality of keypoints to a boundary of the anatomic structure; training a model, using data in the one or more images and the computed distances, for predicting a boundary in the anatomic structure in an image of a patient's anatomy; receiving the image of the patient's anatomy including the anatomic structure; estimating a segmentation boundary in the anatomic structure in the image of the patient's anatomy; and predicting, using the trained model, a boundary location in the anatomic structure in the image of the patient's anatomy by generating a regression of distances from keypoints in the anatomic structure in the image of the patient's anatomy to the estimated boundary.
Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
59.
SYSTEMS AND METHODS FOR PATIENT-SPECIFIC IMAGING AND MODELING OF DRUG DELIVERY
Systems and methods are disclosed for providing personalized chemotherapy and drug delivery using computational fluid dynamics and medical imaging with machine learning from a vascular anatomical model. One method includes receiving a patient-specific anatomical model of at least one vessel of the patient and a target tissue where a drug is to be supplied; receiving patient-specific information defining the administration of a drug; deriving patient-specific data from the patient specific anatomical model and/or the patient; determining one or more blood flow characteristics in a vascular network leading to the one or more locations in the target tissue where drug delivery data will be estimated or measured, using the patient-specific anatomical model and the patient-specific data; and computing drug delivery data at the one or more locations in the target tissue using transportation, spatial, and/or temporal distribution of the drug particles.
G16C 20/30 - Prediction of properties of chemical compounds, compositions or mixtures
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 20/10 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to drugs or medications, e.g. for ensuring correct administration to patients
60.
SYSTEMS AND METHODS FOR IMAGE PROCESSING TO DETERMINE BLOOD FLOW
Embodiments include systems and methods for determining cardiovascular information for a patient. A method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of the patient's vasculature based on the patient-specific data; and creating a computational model of a blood flow characteristic based on the anatomic model. The method also includes identifying one or more of an uncertain parameter, an uncertain clinical variable, and an uncertain geometry; modifying a probability model based on one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry; determining a blood flow characteristic within the patient's vasculature based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature; and calculating, based on the probability model and the determined blood flow characteristic, a sensitivity of the determined fractional flow reserve to one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
Embodiments include systems and methods for determining cardiovascular information for a patient. A method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of the patient's vasculature based on the patient-specific data; and creating a computational model of a blood flow characteristic based on the anatomic model. The method also includes identifying one or more of an uncertain parameter, an uncertain clinical variable, and an uncertain geometry; modifying a probability model based on one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry; determining a blood flow characteristic within the patient's vasculature based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature; and calculating, based on the probability model and the determined blood flow characteristic, a sensitivity of the determined fractional flow reserve to one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
Systems and methods are disclosed for evaluating a patient with vascular disease. One method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of a location of disease in the patient's vasculature based on the received patient-specific data; identifying one or more changes in geometry of the anatomic model based on a modeled progression or regression of disease at the location; calculating one or more values of a blood flow characteristic within the patient's vasculature using a computational model based on the identified one or more changes in geometry of the anatomic model; and generating an electronic graphical display of a relationship between the one or more values of the calculated blood flow characteristic and the identified one or more changes in geometry of the anatomic model.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
63.
SYSTEMS AND METHODS FOR IMAGE PROCESSING TO DETERMINE BLOOD FLOW
Embodiments include systems and methods for determining cardiovascular information for a patient. A method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of the patient's vasculature based on the patient-specific data; and creating a computational model of a blood flow characteristic based on the anatomic model. The method also includes identifying one or more of an uncertain parameter, an uncertain clinical variable, and an uncertain geometry; modifying a probability model based on one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry; determining a blood flow characteristic within the patient's vasculature based on the anatomic model and the computational model of the blood flow characteristic of the patient's vasculature; and calculating, based on the probability model and the determined blood flow characteristic, a sensitivity of the determined fractional flow reserve to one or more of the identified uncertain parameter, uncertain clinical variable, or uncertain geometry.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
Systems and methods are disclosed for evaluating a patient with vascular disease. One method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of a location of disease in the patient's vasculature based on the received patient-specific data; identifying one or more changes in geometry of the anatomic model based on a modeled progression or regression of disease at the location; calculating one or more values of a blood flow characteristic within the patient's vasculature using a computational model based on the identified one or more changes in geometry of the anatomic model; and generating an electronic graphical display of a relationship between the one or more values of the calculated blood flow characteristic and the identified one or more changes in geometry of the anatomic model.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
65.
METHOD AND SYSTEM FOR IMAGE PROCESSING TO DETERMINE BLOOD FLOW
Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.
A61B 34/00 - Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
G06T 7/149 - Segmentation; Edge detection involving deformable models, e.g. active contour models
G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G06F 30/20 - Design optimisation, verification or simulation
G06F 30/23 - Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
G16H 70/00 - ICT specially adapted for the handling or processing of medical references
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
A61M 5/00 - Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm rests
G06K 9/52 - Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
G06T 17/20 - Wire-frame description, e.g. polygonalisation or tessellation
G01R 33/56 - Image enhancement or correction, e.g. subtraction or averaging techniques
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
66.
Method and system for image processing to determine blood flow
Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.
A61B 34/00 - Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
G06T 7/149 - Segmentation; Edge detection involving deformable models, e.g. active contour models
G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G06F 30/20 - Design optimisation, verification or simulation
G06F 30/23 - Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
G16H 70/00 - ICT specially adapted for the handling or processing of medical references
G06V 20/69 - Microscopic objects, e.g. biological cells or cellular parts
G06V 10/42 - Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
G06V 10/40 - Extraction of image or video features
G06V 10/44 - Local feature extraction by analysis of parts of the pattern, e.g. by detecting edges, contours, loops, corners, strokes or intersections; Connectivity analysis, e.g. of connected components
G06F 30/28 - Design optimisation, verification or simulation using fluid dynamics, e.g. using Navier-Stokes equations or computational fluid dynamics [CFD]
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
A61M 5/00 - Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm rests
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
G06T 17/20 - Wire-frame description, e.g. polygonalisation or tessellation
G01R 33/56 - Image enhancement or correction, e.g. subtraction or averaging techniques
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
A61B 90/00 - Instruments, implements or accessories specially adapted for surgery or diagnosis and not covered by any of the groups , e.g. for luxation treatment or for protecting wound edges
G06V 10/46 - Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features
67.
SYSTEMS AND METHODS FOR USING GEOMETRY SENSITIVITY INFORMATION FOR GUIDING WORKFLOW
Systems and methods are disclosed for using geometry sensitivity information for guiding workflows in order to produce reliable models and quantities of interest. One method includes determining a geometric model associated with a target object; determining one or more quantities of interest; determining sensitivity information associated with one or more subdivisions of the geometric model and the one or more quantities of interest; and generating, using a processor, a workflow based on the sensitivity information.
G06Q 10/06 - Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
G16B 15/00 - ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G06F 30/33 - Design verification, e.g. functional simulation or model checking
68.
METHOD AND SYSTEM FOR IMAGE PROCESSING TO DETERMINE BLOOD FLOW
Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.
A61B 34/00 - Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
G06T 7/70 - Determining position or orientation of objects or cameras
G06T 7/73 - Determining position or orientation of objects or cameras using feature-based methods
G06T 7/149 - Segmentation; Edge detection involving deformable models, e.g. active contour models
G06T 7/62 - Analysis of geometric attributes of area, perimeter, diameter or volume
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G06F 30/20 - Design optimisation, verification or simulation
G06F 30/23 - Design optimisation, verification or simulation using finite element methods [FEM] or finite difference methods [FDM]
G16H 70/00 - ICT specially adapted for the handling or processing of medical references
G06T 11/20 - Drawing from basic elements, e.g. lines or circles
A61M 5/00 - Devices for bringing media into the body in a subcutaneous, intra-vascular or intramuscular way; Accessories therefor, e.g. filling or cleaning devices, arm rests
G06K 9/52 - Extraction of features or characteristics of the image by deriving mathematical or geometrical properties from the whole image
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
A61B 5/11 - Measuring movement of the entire body or parts thereof, e.g. head or hand tremor or mobility of a limb
G06T 17/20 - Wire-frame description, e.g. polygonalisation or tessellation
G01R 33/56 - Image enhancement or correction, e.g. subtraction or averaging techniques
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 10/40 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for data related to laboratory analysis, e.g. patient specimen analysis
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
69.
SYSTEMS AND METHODS FOR SIMULATION OF OCCLUDED ARTERIES AND OPTIMIZATION OF OCCLUSION-BASED TREATMENTS
Systems and methods are disclosed for simulation of occluded arteries and/or optimization of occlusion-based treatments. One method includes obtaining a patient-specific anatomic model of a patient's vasculature; obtaining an initial computational model of blood flow through the patient's vasculature based on the patient-specific anatomic model; obtaining a post-treatment computational model by modifying portions of the initial computational model based on an occlusion-based treatment; generating a pre-treatment blood flow characteristic using the initial computational model or computing a post-treatment blood flow using the post-treatment computational model; and outputting a representation of the pre-treatment blood flow characteristic or the post-treatment blood flow characteristic.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 20/40 - ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
G16H 40/67 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
G06F 17/18 - Complex mathematical operations for evaluating statistical data
70.
SYSTEMS AND METHODS FOR VASCULAR DIAGNOSIS USING BLOOD FLOW MAGNITUDE AND/OR DIRECTION
Systems and methods are disclosed for diagnosing and treatment planning for vascular steal syndromes and retrograde flow. One method includes receiving a reference blood flow direction at a location in a reference vasculature; determining a patient-related blood flow direction at a location in a patient's vasculature corresponding to the location in the reference vasculature; determining a difference in direction, between the reference blood flow direction of the reference vasculature and the patient-related blood flow direction of the patient's vasculature; and generating a representation of the location in the patient's vasculature associated with the difference in direction between the reference blood flow direction and the patient-related blood flow direction, or generating a treatment recommendation for the patient's vasculature based on the difference in direction between the reference blood flow direction and the patient-related blood flow direction.
A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
71.
Systems and methods for anatomic structure segmentation in image analysis
Systems and methods are disclosed for anatomic structure segmentation in image analysis, using a computer system. One method includes: receiving an annotation and a plurality of keypoints for an anatomic structure in one or more images; computing distances from the plurality of keypoints to a boundary of the anatomic structure; training a model, using data in the one or more images and the computed distances, for predicting a boundary in the anatomic structure in an image of a patient's anatomy; receiving the image of the patient's anatomy including the anatomic structure; estimating a segmentation boundary in the anatomic structure in the image of the patient's anatomy; and predicting, using the trained model, a boundary location in the anatomic structure in the image of the patient's anatomy by generating a regression of distances from keypoints in the anatomic structure in the image of the patient's anatomy to the estimated boundary.
Systems and methods are disclosed for assessing cardiovascular disease and treatment effectiveness based on adipose tissue. One method includes identifying a vascular bed of interest in a patient's vasculature; receiving a medical image of the patient's identified vascular bed of interest; identifying adipose tissue in the received medical image; receiving a geometric vascular model comprising a representation of the patient's identified vascular bed of interest; and computing an inflammation index associated with the geometric vascular model, using the identified adipose tissue.
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
73.
Systems and methods for identifying and modeling unresolved vessels in image-based patient-specific hemodynamic models
Systems and methods are disclosed for identifying and modeling unresolved vessels, and the effects thereof, in image-based patient-specific hemodynamic models. One method includes: receiving, in an electronic storage medium, one or more patient-specific anatomical models representing at least a vessel of a patient; determining, using a processor, the values and characteristics of one or more patient-specific morphometric features in the one or more patient-specific anatomical models; modifying the patient-specific anatomical model using the determined patient-specific morphometric features; and outputting, one or more of, a modified patient-specific anatomical model or a patient-specific morphometric feature to an electronic storage medium or display.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16Z 99/00 - Subject matter not provided for in other main groups of this subclass
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
74.
SYSTEMS AND METHODS FOR VESSEL REACTIVITY TO GUIDE DIAGNOSIS OR TREATMENT OF CARDIOVASCULAR DISEASE
Systems and methods are disclosed for using vessel reactivity to guide diagnosis or treatment for cardiovascular disease. One method includes receiving a patient-specific vascular model of a patient's anatomy, including at least one vessel of the patient; determining, by measurement or estimation, a first vessel size at one or more locations of a vessel of the patient-specific vascular model at a first physiological state; determining a second vessel size at the one or more locations of the vessel of the patient-specific vascular model at a second physiological state using a simulation or learned information; comparing the first vessel size to the corresponding second vessel size; and estimating a characteristic of the vessel of the patient-specific vascular model based on the comparison.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
75.
Systems and methods for diagnosis and assessment of cardiovascular disease by comparing arterial supply capacity to end-organ demand
Systems and methods are disclosed for to determining a blood supply and blood demand. One method includes receiving a patient-specific model of vessel geometry of at least a portion of a coronary artery, wherein the model is based on patient-specific image data of at least a portion of a patient's heart having myocardium; determining a coronary blood supply based on the patient-specific model; determining at least a portion of the myocardium corresponding to the coronary artery; determining a myocardial blood demand based on either a mass or a volume of the portion of the myocardium, or based on perfusion imaging of the portion of the myocardium; and determining a relationship between the coronary blood supply and the myocardial blood demand.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
Systems and methods are disclosed for displaying health data during a security timeout. One method includes: displaying an interactive interface; receiving a data type included in the display; detecting a timeout of the interactive interface; hiding or removing the data type from the display in response to the timeout; and initiating an extended timeout including the display with the data type removed.
H04L 29/08 - Transmission control procedure, e.g. data link level control procedure
H04L 29/06 - Communication control; Communication processing characterised by a protocol
G16H 40/60 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G06F 21/62 - Protecting access to data via a platform, e.g. using keys or access control rules
H04N 1/00 - PICTORIAL COMMUNICATION, e.g. TELEVISION - Details thereof
77.
System and methods for estimation of blood flow characteristics using reduced order model and machine learning
Systems and methods are disclosed for determining blood flow characteristics of a patient. One method includes: receiving, in an electronic storage medium, patient-specific image data of at least a portion of vasculature of the patient having geometric features at one or more points; generating a patient-specific reduced order model from the received image data, the patient-specific reduced order model comprising estimates of impedance values and a simplification of the geometric features at the one or more points of the vasculature of the patient; creating a feature vector comprising the estimates of impedance values and geometric features for each of the one or more points of the patient-specific reduced order model; and determining blood flow characteristics at the one or more points of the patient-specific reduced order model using a machine learning algorithm trained to predict blood flow characteristics based on the created feature vectors at the one or more points.
G06K 9/00 - Methods or arrangements for reading or recognising printed or written characters or for recognising patterns, e.g. fingerprints
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/70 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
Embodiments include a system for determining cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart, and create a three-dimensional model representing at least a portion of the patient's heart based on the patient-specific data. The at least one computer system may be further configured to create a physics-based model relating to a blood flow characteristic of the patient's heart and determine a fractional flow reserve within the patient's heart based on the three-dimensional model and the physics-based model.
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/027 - Measuring blood flow using electromagnetic means, e.g. electromagnetic flow meter using catheters
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
79.
Systems and methods for predicting coronary plaque vulnerability from patient specific anatomic image data
Systems and methods are disclosed for predicting coronary plaque vulnerability, using a computer system. One method includes acquiring anatomical image data of at least part the patient's vascular system; performing, using a processor, one or more image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis on the anatomical image data; predicting, using the processor, a coronary plaque vulnerability present in the patient's vascular system, wherein predicting the coronary plaque vulnerability includes calculating an adverse plaque characteristic based on results of the one or more of image characteristics analysis, geometrical analysis, computational fluid dynamics analysis, and structural mechanics analysis of the anatomical image data; and reporting, using the processor, the calculated adverse plaque characteristic.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
A61B 8/12 - Diagnosis using ultrasonic, sonic or infrasonic waves in body cavities or body tracts, e.g. by using catheters
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
Systems and methods are disclosed for assessing organ and/or tissue transplantation by estimating blood flow through a virtual transplant model by receiving a patient-specific anatomical model of the intended transplant recipient; receiving a patient-specific anatomical model of the intended transplant donor, the model including the vasculature of the organ or tissue that is intended to be transplanted to the recipient; constructing a unified model of the connected system post transplantation, the connected system including the transplanted organ or tissue from the intended transplant donor and the vascular system of the intended transplant recipient; receiving one or more blood flow characteristics of the connected system; assessing the suitability for an actual organ or tissue transplantation using the received blood flow characteristics; and outputting the assessment into an electronic storage medium or display.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
81.
Systems and methods for anatomical modeling using information obtained from a medical procedure
Systems and methods are disclosed herein for anatomical modeling using information obtained during a medical procedure, whereby an initial anatomical model is generated or obtained, a correspondence is determined between the initial model and additional data and/or measurements from an invasive or noninvasive procedure, and, if a discrepancy is found between the initial model and the additional data, the anatomical model is updated to incorporate the additional data and reduce the discrepancy.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
82.
Systems and methods for an interactive tool for determining and visualizing a functional relationship between a vascular network and perfused tissue
Systems and methods are disclosed for creating an interactive tool for determining and displaying a functional relationship between a vascular network and an associated perfused tissue. One method includes receiving a patient-specific vascular model of a patient's anatomy, including at least one vessel of the patient; receiving a patient-specific tissue model, including a tissue region associated with the at least one vessel of the patient; receiving a selected area of the vascular model or a selected area of the tissue model; and generating a display of a region of the tissue model corresponding to the selected area of the vascular model or a display of a portion of the vascular model corresponding to the selected area of the tissue model, respectively.
G06T 15/00 - 3D [Three Dimensional] image rendering
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 34/00 - Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
G06F 3/048 - Interaction techniques based on graphical user interfaces [GUI]
83.
SYSTEMS AND METHODS FOR REPORTING BLOOD FLOW CHARACTERISTICS
Embodiments include a system for displays cardiovascular information for a patient. The system may include at least one computer system configured to receive patient-specific data regarding a geometry of the patient's heart and create a model representing at least a portion of the patient's heart based on the patient-specific data. The computer system may determine at least one value of the blood flow characteristic within the patient's heart based on the model. The computer system may also display a report comprising a representation of at least one artery corresponding to at least a portion the model, and display one or more indicators of the value of the blood flow characteristic on a corresponding portion of the at least one artery.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
84.
Method and system for providing information from a patient-specific model of blood flow
Embodiments include a system for providing blood flow information for a patient. The system may include at least one computer system including a touchscreen. The at least one computer system may be configured to display, on the touchscreen, a three-dimensional model representing at least a portion of an anatomical structure of the patient based on patient-specific data. The at least one computer system may also be configured to receive a first input relating to a first location on the touchscreen indicated by at least one pointing object controlled by a user, and the first location on the touchscreen may indicate a first location on the displayed three-dimensional model. The at least one computer system may be further configured to display first information on the touchscreen, and the first information may indicate a blood flow characteristic at the first location.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16B 5/00 - ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
G06T 19/20 - Editing of 3D images, e.g. changing shapes or colours, aligning objects or positioning parts
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G06F 30/20 - Design optimisation, verification or simulation
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G06F 3/04815 - Interaction with a metaphor-based environment or interaction object displayed as three-dimensional, e.g. changing the user viewpoint with respect to the environment or object
G06F 3/0488 - Interaction techniques based on graphical user interfaces [GUI] using specific features provided by the input device, e.g. functions controlled by the rotation of a mouse with dual sensing arrangements, or of the nature of the input device, e.g. tap gestures based on pressure sensed by a digitiser using a touch-screen or digitiser, e.g. input of commands through traced gestures
G06T 15/00 - 3D [Three Dimensional] image rendering
A61B 5/021 - Measuring pressure in heart or blood vessels
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
Systems and methods are disclosed for evaluating a patient with vascular disease. One method includes receiving patient-specific data regarding a geometry of the patient's vasculature; creating an anatomic model representing at least a portion of a location of disease in the patient's vasculature based on the received patient-specific data; identifying one or more changes in geometry of the anatomic model based on a modeled progression or regression of disease at the location; calculating one or more values of a blood flow characteristic within the patient's vasculature using a computational model based on the identified one or more changes in geometry of the anatomic model; and generating an electronic graphical display of a relationship between the one or more values of the calculated blood flow characteristic and the identified one or more changes in geometry of the anatomic model.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16B 45/00 - ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 40/20 - ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
86.
Systems and methods for anatomic structure segmentation in image analysis
Systems and methods are disclosed for anatomic structure segmentation in image analysis, using a computer system. One method includes: receiving an annotation and a plurality of keypoints for an anatomic structure in one or more images; computing distances from the plurality of keypoints to a boundary of the anatomic structure; training a model, using data in the one or more images and the computed distances, for predicting a boundary in the anatomic structure in an image of a patient's anatomy; receiving the image of the patient's anatomy including the anatomic structure; estimating a segmentation boundary in the anatomic structure in the image of the patient's anatomy; and predicting, using the trained model, a boundary location in the anatomic structure in the image of the patient's anatomy by generating a regression of distances from keypoints in the anatomic structure in the image of the patient's anatomy to the estimated boundary.
A computer implemented method for assessing an arterio-venous malformation (AVM) may include, for example, receiving a patient-specific model of a portion of an anatomy of a patient; using a computer processor to analyze the patient-specific model for identifying one or more blood vessels associated with the AVM, in the patient-specific model; and estimating a risk of an undesirable outcome caused by the AVM, by performing computer simulations of blood flow through the one or more blood vessels associated with the AVM in the patient-specific model.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
A61B 5/055 - Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves involving electronic [EMR] or nuclear [NMR] magnetic resonance, e.g. magnetic resonance imaging
88.
Systems and methods for medical acquisition processing and machine learning for anatomical assessment
Systems and methods are disclosed for determining anatomy directly from raw medical acquisitions using a machine learning system. One method includes obtaining raw medical acquisition data from transmission and collection of energy and particles traveling through and originating from bodies of one or more individuals; obtaining a parameterized model associated with anatomy of each of the one or more individuals; determining one or more parameters for the parameterized model, wherein the parameters are associated with the raw medical acquisition data; training a machine learning system to predict one or more values for each of the determined parameters of the parameterized model, based on the raw medical acquisition data; acquiring a medical acquisition for a selected patient; and using the trained machine learning system to determine a parameter value for a patient-specific parameterized model of the patient.
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
Systems and methods are disclosed for blood flow simulation. For example, a method may include performing a plurality of blood flow simulations using a first model of vascular blood flow, each of the plurality of blood flow simulations simulating blood flow in a vasculature of a patient or a geometry based on the vasculature of the patient; based on results of the plurality of blood flow simulations, generating a response surface mapping one or more first parameters of the first model to one or more second parameters of a reduced order model of vascular blood; determining values for the one or more parameters of the reduced order model mapped, by the response surface, from parameter values representing a modified state of the vasculature; and performing simulation using the reduced order model parameterized by the determined values, to determine a blood flow characteristic of the modified state of the vasculature.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
90.
System and method for image-based object modeling using multiple image acquisitions or reconstructions
Systems and methods are disclosed for integrating imaging data from multiple sources to create a single, accurate model of a patient's anatomy. One method includes receiving a representation of a target object for modeling; determining one or more first anatomical parameters of the target anatomical object from at least one of one or more first images of the target anatomical object; determining one or more second anatomical parameters of the target anatomical object from at least one of one or more second images of the target anatomical object; updating the one or more first anatomical parameters based at least on the one or more second anatomical parameters; and generating a model of the target anatomical object based on the updated first anatomical parameters.
Systems and methods are disclosed for blood flow simulation. For example, a method may include performing a plurality of blood flow simulations using a first model of vascular blood flow, each of the plurality of blood flow simulations simulating blood flow in a vasculature of a patient or a geometry based on the vasculature of the patient; based on results of the plurality of blood flow simulations, generating a response surface mapping one or more first parameters of the first model to one or more second parameters of a reduced order model of vascular blood; determining values for the one or more parameters of the reduced order model mapped, by the response surface, from parameter values representing a modified state of the vasculature; and performing simulation using the reduced order model parameterized by the determined values, to determine a blood flow characteristic of the modified state of the vasculature.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
92.
Systems and methods for analyzing and processing digital images to estimate vessel characteristics
Systems and methods are disclosed for determining individual-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, individual-specific anatomic data and blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the individual-specific anatomic data and blood flow characteristics for each of the plurality of individuals; relating, based on the executed machine learning algorithm, each individual's individual-specific anatomic data to functional estimates of blood flow characteristics; acquiring, for an individual and individual-specific anatomic data of at least part of the individual's vascular system; and for at least one point in the individual's individual-specific anatomic data, determining a blood flow characteristic of the individual, using relations from the step of relating individual-specific anatomic data to functional estimates of blood flow characteristics.
A61B 6/00 - Apparatus for radiation diagnosis, e.g. combined with radiation therapy equipment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/0205 - Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
A61B 5/021 - Measuring pressure in heart or blood vessels
A61B 5/107 - Measuring physical dimensions, e.g. size of the entire body or parts thereof
A61B 5/00 - Measuring for diagnostic purposes ; Identification of persons
Systems and methods are disclosed for blood flow simulation. For example, a method may include performing a plurality of blood flow simulations using a first model of vascular blood flow, each of the plurality of blood flow simulations simulating blood flow in a vasculature of a patient or a geometry based on the vasculature of the patient; based on results of the plurality of blood flow simulations, generating a response surface mapping one or more first parameters of the first model to one or more second parameters of a reduced order model of vascular blood; determining values for the one or more parameters of the reduced order model mapped, by the response surface, from parameter values representing a modified state of the vasculature; and performing simulation using the reduced order model parameterized by the determined values, to determine a blood flow characteristic of the modified state of the vasculature.
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 30/40 - ICT specially adapted for the handling or processing of medical images for processing medical images, e.g. editing
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
Computer-implemented methods are disclosed for assessing the effect of musculoskeletal activities on disease and/or clinical events, the method comprising: receiving a patient-specific vascular and musculoskeletal model of a patient's anatomy, including at least one vessel of the patient; receiving at least one characteristic of the patient's musculoskeletal activity; generating or updating a computational anatomic vascular and musculoskeletal model of the patient's anatomy based on the received at least one characteristic of musculoskeletal activity; performing at least one of a computational fluid dynamics analysis or a structural mechanics simulation on the computational anatomic vascular and musculoskeletal model; and estimating at least one of the patient's risk of disease or clinical events based on the performed computational fluid dynamics analysis and/or structural mechanics simulation. Systems and computer readable media for executing these methods are also disclosed.
A61B 34/00 - Computer-aided surgery; Manipulators or robots specially adapted for use in surgery
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
A61B 34/10 - Computer-aided planning, simulation or modelling of surgical operations
95.
Methods and systems for assessing image quality in modeling of patient anatomic or blood flow characteristics
Systems and methods are disclosed for assessing the quality of medical images of at least a portion of a patient's anatomy, using a computer system. One method includes receiving one or more images of at least a portion of the patient's anatomy; determining, using a processor of the computer system, one or more image properties of the received images; performing, using a processor of the computer system, anatomic localization or modeling of at least a portion of the patient's anatomy based on the received images; obtaining an identification of one or more image characteristics associated with an anatomic feature of the patient's anatomy based on the anatomic localization or modeling; and calculating, using a processor of the computer system, an image quality score based on the one or more image properties and the one or more image characteristics.
A61B 8/08 - Detecting organic movements or changes, e.g. tumours, cysts, swellings
G01R 33/563 - Image enhancement or correction, e.g. subtraction or averaging techniques of moving material, e.g. flow-contrast angiography
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
96.
Systems and methods for estimating hemodynamic forces acting on plaque and monitoring risk
Computer-implemented methods are disclosed for estimating values of hemodynamic forces acting on plaque or lesions. One method includes: receiving one or more patient-specific parameters of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion; constructing a patient-specific geometric model of at least a portion of a patient's vasculature that is prone to plaque progression, rupture, or erosion, using the received one or more patient-specific parameters; estimating, using one or more processors, the values of hemodynamic forces at one or more points on the patient-specific geometric model, using the patient-specific parameters and geometric model by measuring, deriving, or obtaining one or more of a pressure gradient and a radius gradient; and outputting the estimated values of hemodynamic forces to an electronic storage medium. Systems and computer readable media for executing these methods are also disclosed.
G16H 50/50 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders
G16H 50/30 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for individual health risk assessment
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
A61B 5/02 - Measuring pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography; Heart catheters for measuring blood pressure
A61B 5/0215 - Measuring pressure in heart or blood vessels by means inserted into the body
97.
SYSTEM ARCHITECTURE AND METHODS FOR ANALYZING HEALTH DATA ACROSS GEOGRAPHIC REGIONS BY PRIORITY USING A DECENTRALIZED COMPUTING PLATFORM
Systems and methods are disclosed for analyzing health data over a decentralized cloud-computing platform. One method for analyzing health data over a decentralized cloud-computing platform includes: receiving a unique case file containing one or more anonymous DICOM object(s) for analysis; setting a priority level for the unique case file based on priorities associated with the one or more anonymous DICOM object(s); uncompressing and validating at least one of the one or more anonymous DICOM object(s); and transmitting an analysis of at least one of the uncompressed and validated anonymous DICOM object(s), the analysis having been completed according to the priority level of the unique case file.
Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).
G16H 30/20 - ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
G16H 10/60 - ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
G16H 15/00 - ICT specially adapted for medical reports, e.g. generation or transmission thereof
G16H 50/20 - ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
G16H 80/00 - ICT specially adapted for facilitating communication between medical practitioners or patients, e.g. for collaborative diagnosis, therapy or health monitoring
99.
SYSTEM ARCHITECTURE AND METHODS FOR ANALYZING HEALTH DATA ACROSS GEOGRAPHIC REGIONS BY PRIORITY USING A DECENTRALIZED COMPUTING PLATFORM
Systems and methods are disclosed for analyzing health data over a decentralized cloud-computing platform. One method for analyzing health data over a decentralized cloud-computing platform includes: receiving a unique case file containing one or more anonymous DICOM object(s) for analysis; setting a priority level for the unique case file based on priorities associated with the one or more anonymous DICOM object(s); uncompressing and validating at least one of the one or more anonymous DICOM object(s); and transmitting an analysis of at least one of the uncompressed and validated anonymous DICOM object(s), the analysis having been completed according to the priority level of the unique case file.
Systems and methods are disclosed for preserving patient privacy while allowing health data to be analyzed, managed, and stored in different geographical areas. One method for managing cross-border health data while preserving patient privacy includes: receiving a DICOM object from a hospital computing device for analysis; generating a unique case identifier for the DICOM object; validating the received DICOM object; if, based on the validation, the received DICOM object is valid, anonymizing the received DICOM object; updating the anonymous DICOM object to include the unique case identifier; compressing the updated DICOM object; and sending the compressed DICOM object to at least one data analysis web service(s).
