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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Bibliografiske detaljer
Udgivet i:Proc Natl Acad Sci U S A
Main Authors: Fehr, Duc, Veeraraghavan, Harini, Wibmer, Andreas, Gondo, Tatsuo, Matsumoto, Kazuhiro, Vargas, Herbert Alberto, Sala, Evis, Hricak, Hedvig, Deasy, Joseph O.
Format: Artigo
Sprog:Inglês
Udgivet: National Academy of Sciences 2015
Fag:
PNAS Plus
Online adgang: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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