Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning

Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning

BackgroundThe presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent indicator of adverse cardiovascular events in patients with cardiovascular diseases. We develop and evaluate the ability to detect cardiac wall motion abnormalities (WMA) from dynamic volume renderings...

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Bibliographic Details
Main Authors: Zhennong Chen, Francisco Contijoch, Gabrielle M. Colvert, Ashish Manohar, Andrew M. Kahn, Hari K. Narayan, Elliot McVeigh
Format: Article
Language:English
Published: Frontiers Media S.A. 2022-07-01
Series:Frontiers in Cardiovascular Medicine
Subjects:
computed tomography
left ventricle (LV)
wall motion abnormality detection
volume rendering (VR)
deep learning
Online Access:https://www.frontiersin.org/articles/10.3389/fcvm.2022.919751/full

Internet

https://www.frontiersin.org/articles/10.3389/fcvm.2022.919751/full

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