Patent ID: 9675301
Date: 2017-06-13
CPC Classifications: A61B,G06T,G16H,Y02A

Claim:
1. A method for automatically selecting or identifying a patient healthcare decision comprising: receiving, using at least one computer system, non-invasively obtained patient-specific data of one or more coronary arteries of the patient; automatically segmenting, using the at least one computer system, one or more geometric features of the one or more coronary arteries of the patient from the non-invasively obtained patient-specific data; automatically analyzing, using the at least one computer system, the one or more geometric features to identify multiple characteristics of the one or more coronary arteries, wherein automatically analyzing the one or more geometric features comprises: automatically evaluating, using the at least one computer system, the identified multiple characteristics by automatically generating a numerical measurement of at least part of each characteristic, wherein automatically evaluating the identified multiple characteristics includes automatically identifying areas of coronary arteries with disease by training a machine learning algorithm using a database of annotated data and executing the machine learning algorithm on the non-invasively obtained patient specific data; automatically executing, using the at least one computer system, an algorithm using the automatically generated numerical measurements of at least part of each characteristic to generate a cardiovascular score quantifying an extent of cardiovascular disease in the one or more coronary arteries; automatically selecting or identifying a healthcare decision to perform coronary artery bypass grafting (CABG) if the cardiovascular score is above an upper threshold value; and automatically selecting or identifying a healthcare decision to perform percutaneous coronary intervention (PCI) if the cardiovascular score is equal to or below the upper threshold value.