Abstract: Anatomical and functional assessment of coronary artery disease (CAD) using machine learning and computational modeling techniques deploying methodologies for non-invasive Fractional Flow Reserve (FFR) quantification based on angiographically derived anatomy and hemodynamics data, relying on machine learning algorithms for image segmentation and flow assessment, and relying on accurate physics-based computational fluid dynamics (CFD) simulation for computation of the FFR.

Abstract: A computer-implemented method and system for assessing vascular disease is disclosed. The disclosure provides receiving angiography image data, including a plurality of image frames captured over a sampling time-period for a subject; identifying a representative image frame from the plurality of image frames; segmenting the plurality of image frames to isolate a vessel region; inferring a plurality of centerline node points associated with a centerline of the vessel; tracking movement of the plurality of centerline node points between successive centerline node points of the plurality of angiogram image frames; registering each segmented frame of the plurality of image frames to the representative image frame; and determining a flow rate of the vessel based in part on a change in length of the vessel represented in successive registered image frames. In embodiments, resultant measurements and results may be displayed upon one or more user interfaces.

Abstract: A computer-implemented method and system for assessing vascular disease is disclosed. The disclosure provides receiving angiography image data, including a plurality of image frames captured over a sampling time-period for a subject; identifying a representative image frame from the plurality of image frames; segmenting the plurality of image frames to isolate a vessel region; inferring a plurality of centerline node points associated with a centerline of the vessel; tracking movement of the plurality of centerline node points between successive centerline node points of the plurality of angiogram image frames; registering each segmented frame of the plurality of image frames to the representative image frame; and determining a flow rate of the vessel based in part on a change in length of the vessel represented in successive registered image frames.