Automated interpretation of the coronary angioscopy with deep convolutional neural networks

Volume: 7, Issue: 1, Pages: e001177 - e001177
Published: May 1, 2020
Abstract
Background Coronary angioscopy (CAS) is a useful modality to assess atherosclerotic changes, but interpretation of the images requires expert knowledge. Deep convolutional neural networks (DCNN) can be used for diagnostic prediction and image synthesis. Methods 107 images from 47 patients, who underwent CAS in our hospital between 2014 and 2017, and 864 images, selected from 142 MEDLINE-indexed articles published between 2000 and 2019, were...
Paper Details
Title
Automated interpretation of the coronary angioscopy with deep convolutional neural networks
Published Date
May 1, 2020
Journal
Volume
7
Issue
1
Pages
e001177 - e001177
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