Patent ID: 9501622
Filing Date: 2016-11-22
CPC Classification: A61B,G06F,G06N,G06T,G16H

Claim Text:
1. A computer-implemented method of determining a sensitivity of a patient's blood flow characteristic to uncertainty in one or more anatomical or geometrical features of the patient, the method comprising: obtaining, for each of a plurality of individuals, a geometric model of at least a portion of a vascular system of each individual; identifying a plurality of vessel regions in each geometric model; determining, for each geometric model, at least one sensitivity of a blood flow characteristic to at least one uncertainty in geometry in one or more of the identified plurality of vessel regions; associating each of the one or more vessel regions with a determined sensitivity; using the determined sensitivities and associated one or more vessel regions in a machine learning algorithm to construct a machine learning predictor for calculating sensitivities of blood flow characteristics to uncertainties; generating, for a patient, a geometric model of at least part of the patient's vascular system using patient-specific imaging data of at least a portion of the patient's vascular system; determining, for the patient, a designation of a blood flow characteristic, and at least one value of uncertainty in the geometry of at least part of the patient's vascular system; identifying a vessel region of interest in the geometric model generated for the patient; and determining a sensitivity of the blood flow characteristic of the patient to the at least one value of uncertainty in the patient's vascular geometry for at least the vessel region of interest in the patient's geometric model, using the machine learning predictor.