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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Shranjeno v:
Bibliografske podrobnosti
izdano v: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
Jezik:Inglês
Izdano: National Academy of Sciences 2015
Teme:
PNAS Plus
Online dostop: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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