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Distinguishing prostate cancer from benign confounders via a cascaded classifier on multi-parametric MRI., , , , , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 9035 of SPIE Proceedings, page 903512. SPIE, (2014)Automated Gleason Grading of Prostate Biopsies using Deep Learning., , , , , , , , and . CoRR, (2019)Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard., , , , , , , , , and . CoRR, (2018)Automated segmentation of epithelial tissue in prostatectomy slides using deep learning., , , and . Medical Imaging: Digital Pathology, volume 10581 of SPIE Proceedings, page 105810S. SPIE, (2018)Automated detection of prostate cancer in digitized whole-slide images of H and E-stained biopsy specimens., , , , , , and . Medical Imaging: Digital Pathology, volume 9420 of SPIE Proceedings, page 94200B. SPIE, (2015)Artificial Intelligence Assistance Significantly Improves Gleason Grading of Prostate Biopsies by Pathologists., , , , , , , , , and 10 other author(s). CoRR, (2020)Evaluation of tongue squamous cell carcinoma resection margins using ex-vivo MR., , , , , , , , , and 2 other author(s). Int. J. Comput. Assist. Radiol. Surg., 12 (5): 821-828 (2017)Effect of calibration on computerized analysis of prostate lesions using quantitative dynamic contrast-enhanced magnetic resonance imaging., , , , , and . Medical Imaging: Computer-Aided Diagnosis, volume 6514 of SPIE Proceedings, page 65140U. SPIE, (2007)