Prostate cancer detection using residual networks.
Ontology highlight
ABSTRACT:
SUBMITTER: Xu H
PROVIDER: S-EPMC7472465 | biostudies-literature | 2019 Oct
REPOSITORIES: biostudies-literature
Publications
Prostate cancer detection using residual networks.
Xu Helen H Baxter John S H JSH Akin Oguz O Cantor-Rivera Diego D
International journal of computer assisted radiology and surgery 20190410 10
<h4>Purpose</h4>To automatically identify regions where prostate cancer is suspected on multi-parametric magnetic resonance images (mp-MRI).<h4>Methods</h4>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.<h4>Results</h4>The residual network achieved a hit or miss accuracy of 93% for lesion detection, with an average ...[more]
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