Using machine learning to predict carotid artery symptoms from CT angiography: A radiomics and deep learning approach

Using machine learning to predict carotid artery symptoms from CT angiography: A radiomics and deep learning approach

Purpose: To assess radiomics and deep learning (DL) methods in identifying symptomatic Carotid Artery Disease (CAD) from carotid CT angiography (CTA) images. We further compare the performance of these novel methods to the conventional calcium score. Methods: Carotid CT angiography (CTA) images from...

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Bibliographic Details
Main Authors: Elizabeth P.V. Le, Mark Y.Z. Wong, Leonardo Rundo, Jason M. Tarkin, Nicholas R. Evans, Jonathan R. Weir-McCall, Mohammed M. Chowdhury, Patrick A. Coughlin, Holly Pavey, Fulvio Zaccagna, Chris Wall, Rouchelle Sriranjan, Andrej Corovic, Yuan Huang, Elizabeth A. Warburton, Evis Sala, Michael Roberts, Carola-Bibiane Schönlieb, James H.F. Rudd
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:European Journal of Radiology Open
Subjects:
AI
Stroke
Radiomics
Machine learning
Carotid artery
Coronary calcium
Online Access:http://www.sciencedirect.com/science/article/pii/S2352047724000492
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