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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Bibliographic Details
Published in: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
Language:Inglês
Published: National Academy of Sciences 2015
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PNAS Plus
Online Access: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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