Automatic classification of prostate cancer Gleason scores from multiparametric magnetic resonance images

Noninvasive, radiological image-based detection and stratification of Gleason patterns can impact clinical outcomes, treatment selection, and the determination of disease status at diagnosis without subjecting patients to surgical biopsies. We present machine learning-based automatic classification...

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Detalles Bibliográficos
Publicado en:Proc Natl Acad Sci U S A
Autores principales: Fehr, Duc, Veeraraghavan, Harini, Wibmer, Andreas, Gondo, Tatsuo, Matsumoto, Kazuhiro, Vargas, Herbert Alberto, Sala, Evis, Hricak, Hedvig, Deasy, Joseph O.
Formato: Artigo
Lenguaje:Inglês
Publicado: National Academy of Sciences 2015
Materias:
PNAS Plus
Acceso en línea:https://ncbi.nlm.nih.gov/pmc/articles/PMC4655555/
https://ncbi.nlm.nih.gov/pubmed/26578786
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1073/pnas.1505935112
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