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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Detalles Bibliográficos
Autores principales: 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
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2020
Materias:
Original Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338814/
https://www.ncbi.nlm.nih.gov/pubmed/32062817
http://dx.doi.org/10.1007/s12021-019-09439-6

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7338814/
https://www.ncbi.nlm.nih.gov/pubmed/32062817
http://dx.doi.org/10.1007/s12021-019-09439-6

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