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Omni-supervised domain adversarial training for white matter hyperintensity segmentation in the UK Biobank

Abstract:

White matter hyperintensities (WMHs, or lesions) appear as hyperintense, localized regions on T2-weighted and FLAIR brain MR images. The heterogeneity in lesion characteristics due to subject-level (e.g., local intensity/contrast) and population-level (e.g., demographic, scanner-related) variations make their segmentation highly challenging. Here, we propose a framework for adapting a state-of-the-art WMH segmentation method with high accuracy from a small, labeled source data (MICCAI WMH seg...

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Publication status:
Published
Peer review status:
Peer reviewed

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Institution:
University of Oxford
Division:
MPLS
Department:
Computer Science
Oxford college:
Worcester College
Role:
Author
Publisher:
IEEE Publisher's website
Pages:
1-4
Host title:
Proceedings of the 19th International Symposium on Biomedical Imaging (ISBI 2022)
Publication date:
2022-04-26
Event title:
19th International Symposium on Biomedical Imaging (ISBI 2022)
Event location:
Kolkata, India
Event website:
https://biomedicalimaging.org/2022/
Event start date:
2022-03-28T00:00:00Z
Event end date:
2022-03-31T00:00:00Z
DOI:
EISBN:
978-1-6654-2923-8
EISSN:
1945-8452
ISSN:
1945-7928
ISBN:
978-1-6654-2924-5
Language:
English
Keywords:
Pubs id:
1261349
Local pid:
pubs:1261349
Deposit date:
2022-06-19

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