Invention Grant
- Patent Title: Method and system for assessing vessel obstruction based on machine learning
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Application No.: US15933854Application Date: 2018-03-23
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Publication No.: US10176575B2Publication Date: 2019-01-08
- Inventor: Ivana Isgum , Majd Zreik , Tim Leiner
- Applicant: UMC Utrecht Holding B.V.
- Applicant Address: NL Maastricht
- Assignee: Pie Medical Imaging B.V.
- Current Assignee: Pie Medical Imaging B.V.
- Current Assignee Address: NL Maastricht
- Agency: Gordon & Jacobson, P.C.
- Main IPC: G06T7/00
- IPC: G06T7/00 ; G06T7/10 ; G06N3/08 ; G06K9/62

Abstract:
Methods and systems are provided for assessing the presence of functionally significant stenosis in one or more coronary arteries, further known as a severity of vessel obstruction. The methods and systems can implement a prediction phase that comprises segmenting at least a portion of a contrast enhanced volume image data set into data segments corresponding to wall regions of the target organ, and analyzing the data segments to extract features that are indicative of an amount of perfusion experiences by wall regions of the target organ. The methods and systems can obtain a feature-perfusion classification (FPC) model derived from a training set of perfused organs, classify the data segments based on the features extracted and based on the FPC model, and provide, as an output, a prediction indicative of a severity of vessel obstruction based on the classification of the features.
Public/Granted literature
- US20180276817A1 Method and System for Assessing Vessel Obstruction Based on Machine Learning Public/Granted day:2018-09-27
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