Health AI Central
Peer-Reviewed Publication
Int J Comput Assist Radiol Surg2019;14(10):1647-1650.October 1, 2019Journal Article

Prostate cancer detection using residual networks.

Helen Xu1, John S H Baxter2, Oguz Akin3, Diego Cantor-Rivera4
1Ezra AI Canada, Unit 310, 545 King St. West, Toronto, Canada.
2Université de Rennes 1, Rennes, France.
3Memorial Sloan Kettering Cancer Center, New York, NY, USA.
4Ezra AI Canada, Unit 310, 545 King St. West, Toronto, Canada. diego@ezra.ai.
PubMed PMC DOI PDF

Abstract

PURPOSE: To automatically identify regions where prostate cancer is suspected on multi-parametric magnetic resonance images (mp-MRI). METHODS: A residual network was implemented based on segmentations from an expert radiologist on T2-weighted, apparent diffusion coefficient map, and high b-value diffusion-weighted images. Mp-MRIs from 346 patients were used in this study. RESULTS: The residual n…

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