Contrast quality control for segmentation task based on deep learning models—Application to stroke lesion in CT imaging

Contrast quality control for segmentation task based on deep learning models—Application to stroke lesion in CT imaging

IntroductionAlthough medical imaging plays a crucial role in stroke management, machine learning (ML) has been increasingly used in this field, particularly in lesion segmentation. Despite advances in acquisition technologies and segmentation architectures, one of the main challenges of subacute str...

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Bibliographic Details
Main Authors: Juliette Moreau, Laura Mechtouff, David Rousseau, Omer Faruk Eker, Yves Berthezene, Tae-Hee Cho, Carole Frindel
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-02-01
Series:Frontiers in Neurology
Subjects:
deep learning
segmentation
quality control
contrast analysis
stroke
CT imaging
Online Access:https://www.frontiersin.org/articles/10.3389/fneur.2025.1434334/full
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https://www.frontiersin.org/articles/10.3389/fneur.2025.1434334/full

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