Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events

Assessing robustness of carotid artery CT angiography radiomics in the identification of culprit lesions in cerebrovascular events

Abstract Radiomics, quantitative feature extraction from radiological images, can improve disease diagnosis and prognostication. However, radiomic features are susceptible to image acquisition and segmentation variability. Ideally, only features robust to these variations would be incorporated into...

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Détails bibliographiques
Auteurs principaux: Elizabeth P. V. Le, Leonardo Rundo, Jason M. Tarkin, Nicholas R. Evans, Mohammed M. Chowdhury, Patrick A. Coughlin, Holly Pavey, Chris Wall, Fulvio Zaccagna, Ferdia A. Gallagher, Yuan Huang, Rouchelle Sriranjan, Anthony Le, Jonathan R. Weir-McCall, Michael Roberts, Fiona J. Gilbert, Elizabeth A. Warburton, Carola-Bibiane Schönlieb, Evis Sala, James H. F. Rudd
Format: article
Langue:EN
Publié: Nature Portfolio 2021
Sujets:
Medicine
R
Science
Q
Accès en ligne:https://doaj.org/article/3c38d77b56a846ac9f44b3d1df1785f4
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https://doaj.org/article/3c38d77b56a846ac9f44b3d1df1785f4

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