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Ultrasound-Based Characterization of Prostate Cancer: An in vivo Clinical Feasibility Study.

, , , , , , , , , , , , , and . MICCAI (2), volume 8150 of Lecture Notes in Computer Science, page 279-286. Springer, (2013)

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Ultrasound-Based Characterization of Prostate Cancer: An in vivo Clinical Feasibility Study., , , , , , , , , and 4 other author(s). MICCAI (2), volume 8150 of Lecture Notes in Computer Science, page 279-286. Springer, (2013)Computer-Aided Prostate Cancer Detection Using Ultrasound RF Time Series: In Vivo Feasibility Study., , , , , , , , , and 4 other author(s). IEEE Trans. Med. Imaging, 34 (11): 2248-2257 (2015)Ultrasound-Based Characterization of Prostate Cancer Using Joint Independent Component Analysis., , , , , , , , , and 6 other author(s). IEEE Trans. Biomed. Eng., 62 (7): 1796-1804 (2015)Fusion of multi-parametric MRI and temporal ultrasound for characterization of prostate cancer: in vivo feasibility study., , , , , , , , , and 9 other author(s). Medical Imaging: Computer-Aided Diagnosis, volume 9785 of SPIE Proceedings, page 97851K. SPIE, (2016)Biomechanically Constrained Surface Registration: Application to MR-TRUS Fusion for Prostate Interventions., , , , , , , , , and 5 other author(s). IEEE Trans. Medical Imaging, 34 (11): 2404-2414 (2015)Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study., , , , , , , , , and 5 other author(s). Medical Imaging: Image-Guided Procedures, volume 9786 of SPIE Proceedings, page 97860K. SPIE, (2016)