Automated White Matter Hyperintensity Segmentation Using Bayesian Model Selection: Assessment and Correlations with Cognitive Change

Accurate, automated white matter hyperintensity (WMH) segmentations are needed for large-scale studies to understand contributions of WMH to neurological diseases. We evaluated Bayesian Model Selection (BaMoS), a hierarchical fully-unsupervised model selection framework for WMH segmentation. We comp...

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Bibliografski detalji
Izdano u:Neuroinformatics
Glavni autori: Fiford, Cassidy M., Sudre, Carole H., Pemberton, Hugh, Walsh, Phoebe, Manning, Emily, Malone, Ian B., Nicholas, Jennifer, Bouvy, Willem H, Carmichael, Owen T., Biessels, Geert Jan, Cardoso, M. Jorge, Barnes, Josephine
Format: Artigo
Jezik:Inglês
Izdano: Springer US 2020
Teme:
Original Article
Online pristup:https://ncbi.nlm.nih.gov/pmc/articles/PMC7338814/
https://ncbi.nlm.nih.gov/pubmed/32062817
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1007/s12021-019-09439-6
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