Deep learning for MRI-based acute and subacute ischaemic stroke lesion segmentation—a systematic review, meta-analysis, and pilot evaluation of key results

Deep learning for MRI-based acute and subacute ischaemic stroke lesion segmentation—a systematic review, meta-analysis, and pilot evaluation of key results

BackgroundSegmentation of ischaemic stroke lesions from magnetic resonance images (MRI) remains a challenging task mainly due to the confounding appearance of these lesions with other pathologies, and variations in their presentation depending on the lesion stage (i.e., hyper-acute, acute, subacute...

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Bibliographic Details
Main Authors: Makram Baaklini, Maria del C. Valdés Hernández
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-06-01
Series:Frontiers in Medical Technology
Subjects:
acute ischaemic stroke
deep learning
MRI
attention mechanisms
lesion segmentation
Online Access:https://www.frontiersin.org/articles/10.3389/fmedt.2025.1491197/full
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