Heartflow, Inc.

Stenomics, Inc.

Skur, Inc.

Michael Singer

Leo John Grady

Gilwoo Choi

Timothy A Fonte

Jin Kim

Adam Cohen

James Creasy

Alan Gushurst

Daniel Chavez

Farid W Saddik

James L Barber

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.

Systems and methods for processing electronic images to evaluate medical images

Systems and methods for estimating ischemia and blood flow characteristics from vessel geometry and physiology

Systems and methods are disclosed for estimating patient-specific blood flow characteristics. One method includes acquiring, for each of a plurality of individuals, a geometric model and estimated blood flow characteristics of at least part of the individual's vascular system; executing a machine learning algorithm on the geometric model and estimated blood flow characteristics for each of the plurality of individuals; identifying, using the machine learning algorithm, features predictive of blood flow characteristics corresponding to a plurality of points in the geometric models; acquiring, for a patient, a geometric model of at least part of the patient's vascular system; and using the identified features to produce estimates of the patient's blood flow characteristic for each of a plurality of points in the patient's geometric model.

Systems and methods for estimating blood flow characteristics from vessel geometry and physiology

A computer-implemented method for simulating blood flow through one or more coronary blood vessels may first involve receiving patient-specific data, including imaging data related to one or more coronary blood vessels, and at least one clinically measured flow parameter. Next, the method may involve generating a digital model of the one or more coronary blood vessels, based at least partially on the imaging data, discretizing the model, applying boundary conditions to a portion of the digital model that contains the one or more coronary blood vessels, and initializing and solving mathematical equations of blood flow through the model to generate computerized flow parameters. Finally, the method may involve comparing the computerized flow parameters with the at least one clinically measured flow parameter.

Modeling and simulation system for optimizing prosthetic heart valve treatment

A machine learning system for evaluating at least one characteristic of a heart valve, an inflow tract, an outflow tract or a combination thereof may include a training mode and a production mode. The training mode may be configured to train a computer and construct a transformation function to predict an unknown anatomical characteristic and/or an unknown physiological characteristic of a heart valve, inflow tract and/or outflow tract, using a known anatomical characteristic and/or a known physiological characteristic the heart valve, inflow tract and/or outflow tract. The production mode may be configured to use the transformation function to predict the unknown anatomical characteristic and/or the unknown physiological characteristic of the heart valve, inflow tract and/or outflow tract, based on the known anatomical characteristic and/or the known physiological characteristic of the heart valve, inflow tract and/or outflow tract.

Machine learning system for assessing heart valves and surrounding cardiovascular tracts

Systems and methods for analyzing and processing digital images to estimate vessel characteristics

A system for noninvasively determining at least one physiological characteristic of a patient may include at least one computer system configured to, using a three-dimensional surface mesh model created using patient-specific imaging data, create a three-dimensional combined surface and volume mesh model, including at least a first model portion that has a different spatial resolution than at least a second model portion. The computer system may be further configured to input the three-dimensional surface and volume mesh model into a fluid simulation system and determine a measurement of the physiological characteristic, using the fluid simulation system.

Method and system for facilitating physiological computations

Systems and methods of image processing to determine flow characteristics

Growing community of inventors

Belmont, CA, United States of America

Michael Singer