A deep learning approach to predict collateral flow in stroke patients using radiomic features from perfusion images

A deep learning approach to predict collateral flow in stroke patients using radiomic features from perfusion images

Collateral circulation results from specialized anastomotic channels which are capable of providing oxygenated blood to regions with compromised blood flow caused by arterial obstruction. The quality of collateral circulation has been established as a key factor in determining the likelihood of a fa...

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Bibliographic Details
Main Authors: Giles Tetteh, Fernando Navarro, Raphael Meier, Johannes Kaesmacher, Johannes C. Paetzold, Jan S. Kirschke, Claus Zimmer, Roland Wiest, Bjoern H. Menze
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-02-01
Series:Frontiers in Neurology
Subjects:
collateral flow
radiomics
perfusion
reinforcement learning
image descriptors
angiography
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2023.1039693/full

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https://www.frontiersin.org/articles/10.3389/fneur.2023.1039693/full

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