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Biopsy-guided learning with deep convolutional neural networks for Prostate Cancer detection on multiparametric MRI.

, , , , , , , , and . ISBI, page 642-645. IEEE, (2017)

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A multiview boosting approach to tissue segmentation., , , , , , and . Medical Imaging: Digital Pathology, volume 9041 of SPIE Proceedings, page 90410R. SPIE, (2014)Multiview boosting digital pathology analysis of prostate cancer., and . Comput. Methods Programs Biomed., (2017)Fusarium Wilt of Radish Detection Using RGB and Near Infrared Images from Unmanned Aerial Vehicles., , , , , , , and . Remote. Sens., 12 (17): 2863 (2020)Domain Generalization in Computational Pathology: Survey and Guidelines., , , , , , , , , and 1 other author(s). CoRR, (2023)XY Network for Nuclear Segmentation in Multi-Tissue Histology Images., , , , and . CoRR, (2018)Improving detection of prostate cancer foci via information fusion of MRI and temporal enhanced ultrasound., , , , , , , , , and 4 other author(s). Int. J. Comput. Assist. Radiol. Surg., 15 (7): 1215-1223 (2020)Transfer learning from RF to B-mode temporal enhanced ultrasound features for prostate cancer detection., , , , , , , , , and 1 other author(s). Int. J. Comput. Assist. Radiol. Surg., 12 (7): 1111-1121 (2017)Deep neural maps for unsupervised visualization of high-grade cancer in prostate biopsies., , , , , , , , , and 4 other author(s). Int. J. Comput. Assist. Radiol. Surg., 14 (6): 1009-1016 (2019)Deep dense multi-path neural network for prostate segmentation in magnetic resonance imaging., , , , and . Int. J. Comput. Assist. Radiol. Surg., 13 (11): 1687-1696 (2018)Correlation of magnetic resonance imaging with digital histopathology in prostate., , , , , , , and . Int. J. Comput. Assist. Radiol. Surg., 11 (4): 657-666 (2016)