Most Edges in Markov Random Fields for White Matter Hyperintensity Segmentation are Worthless

The time and space complexities of Markov random field (MRF) algorithms for image segmentation increase with the number of edges that represent statistical dependencies between adjacent pixels. This has made MRFs too computationally complex for cutting-edge applications such as joint segmentation of...

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Главные авторы: Schwarz, Christopher G., Fletcher, Evan, Singh, Baljeet, Liu, Amy, Smith, Noel, DeCarli, Charles, Carmichael, Owen
Формат: Artigo
Язык:Inglês
Опубликовано: 2012
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Article
Online-ссылка:https://ncbi.nlm.nih.gov/pmc/articles/PMC3775838/
https://ncbi.nlm.nih.gov/pubmed/23366478
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/EMBC.2012.6346517
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