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Triplanar ensemble U-Net model for white matter hyperintensities segmentation on MR images

Abstract:

White matter hyperintensities (WMHs) have been associated with various cerebrovascular and neurodegenerative diseases. Reliable quantification of WMHs is essential for understanding their clinical impact in normal and pathological populations. Automated segmentation of WMHs is highly challenging due to heterogeneity in WMH characteristics between deep and periventricular white matter, presence of artefacts and differences in the pathology and demographics of populations. In this work, we prop...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1016/j.media.2021.102184

Authors


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Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Oxford college:
St Edmund Hall
Role:
Author
More by this author
Institution:
University of Oxford
Division:
MSD
Department:
Clinical Neurosciences
Role:
Author
Parkinson's UK More from this funder
Publisher:
Elsevier Publisher's website
Journal:
Medical Image Analysis Journal website
Volume:
73
Article number:
102184
Publication date:
2021-07-18
Acceptance date:
2021-07-16
DOI:
EISSN:
1361-8423
ISSN:
1361-8415
Pmid:
34325148
Language:
English
Keywords:
Pubs id:
1188930
Local pid:
pubs:1188930
Deposit date:
2022-03-15

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