Self-Trained Supervised Segmentation of Subcortical Brain Structures Using Multispectral Magnetic Resonance Images

The aim of this paper is investigate the feasibility of automatically training supervised methods, such as k-nearest neighbor (kNN) and principal component discriminant analysis (PCDA), and to segment the four subcortical brain structures: caudate, thalamus, pallidum, and putamen. The adoption of su...

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Detalles Bibliográficos
Autores principales: Larobina, Michele, Murino, Loredana, Cervo, Amedeo, Alfano, Bruno
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2015
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4637150/
https://www.ncbi.nlm.nih.gov/pubmed/26583131
http://dx.doi.org/10.1155/2015/764383

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4637150/
https://www.ncbi.nlm.nih.gov/pubmed/26583131
http://dx.doi.org/10.1155/2015/764383

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