公开(公告)号：US20220277456A1

公开(公告)日：2022-09-01

申请号：US17606996

申请日：2020-04-30

Applicant: CAMBRIDGE ENTERPRISE LIMITED

Inventor： Adam WOOLF ,  Martin BENNETT

IPC: G06T7/00 ,  G06V10/764 ,  G06V10/82 ,  G06V10/40 ,  G06V10/774 ,  G06V10/766 ,  A61B5/00 ,  G16H30/20

Abstract: Embodiments of the present techniques provide apparatus and methods for analysing intracoronary images, for example to predict the likelihood of a disease, disease presentation or event, and/or to track performance of a drug or other treatment. The method may comprise: for each image in the set of images of a coronary artery: classifying the image, using a first neural network, for the presence or absence of diseased tissue; when the image is classified as having diseased tissue present, classifying the image, using a second neural network, for the presence or absence of an artefact; determining whether to analyse the image based on the classifying steps; when the image is to be analysed, analysing the image by identifying, using a third neural network, one or more features of interest in a coronary artery tissue; and measuring each identified feature of interest.

公开(公告)号：US20240281977A1

公开(公告)日：2024-08-22

申请号：US18652327

申请日：2024-05-01

Applicant: CAMBRIDGE ENTERPRISE LIMITED

Inventor： Adam WOOLF ,  Martin BENNETT

IPC: G06T7/00 ,  G06T5/20 ,  G06T5/40 ,  G06T5/60 ,  G06T7/11 ,  G06T7/13 ,  G06T7/136 ,  G06V10/26 ,  G06V10/32 ,  G06V10/36 ,  G06V10/54 ,  G06V10/75 ,  G06V10/764 ,  G06V10/82 ,  G16H50/20

CPC classification number: G06T7/0016 ,  G06T5/20 ,  G06T5/40 ,  G06T5/60 ,  G06T7/11 ,  G06T7/13 ,  G06T7/136 ,  G06V10/26 ,  G06V10/32 ,  G06V10/36 ,  G06V10/54 ,  G06V10/758 ,  G06V10/764 ,  G06V10/82 ,  G16H50/20 ,  G06T2207/10101 ,  G06T2207/20004 ,  G06T2207/20032 ,  G06T2207/20036 ,  G06T2207/20081 ,  G06T2207/30048 ,  G06T2207/30101 ,  G06V2201/03

Abstract: Disclosed is a method for analyzing a set of images of a coronary artery tissue. The method comprises segmenting the images for the presence of normal artery features and those associated with OCT, correcting artifacts, and optimizing the images. The method further comprises segmenting the diseased tissue into distinct tissue types, and measuring features of interests of the segmented tissue types. The method further comprises compiling a first set of measurements for each identified feature of interest at a first time, and a second set of measurements at a second time subsequent to the first time. The method further comprises determining changes in the coronary artery tissue, indicative of progression or regression of a diseased state, or prediction of multiple adverse cardiovascular events (MACE) such as cardiac death or myocardial infarction.