Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for...
Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia
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Public Library of Science (PLoS)
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English
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Public Library of Science (PLoS)
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PurposeTo validate the diagnostic performance of commercially available, deep learning-based automatic white matter hyperintensity (WMH) segmentation algorithm for classifying the grades of the Fazekas scale and differentiating subcortical vascular dementia.MethodsThis retrospective, observational, single-institution study investigated the diagnost...
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Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia
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TN_cdi_doaj_primary_oai_doaj_org_article_96e02c25ee65428fb7a903f432b377fc
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https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_doaj_primary_oai_doaj_org_article_96e02c25ee65428fb7a903f432b377fc
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1932-6203
DOI
10.1371/journal.pone.0274562
