Convolutional Neural Networks (CNNs) work very well for supervised learning problems when the training dataset is representative of the variations expected to be encountered at test time. In medical image segmentation, this premise is violated when t...
To elucidate factors contributing to early urinary continence recovery after retzius-sparing robot-assisted radical prostatectomy (RS-RARP) by evaluating postoperative pelvic anatomical features between RS-RARP and conventional RARP (CON-RARP). We ...
International journal of urology : official journal of the Japanese Urological Association
Sep 24, 2020
OBJECTIVES: To analyze the correlation between periprostatic fat thickness on multiparametric magnetic resonance imaging and upstaging from cT1/2 to pT3 in robot-assisted radical prostatectomy.
BACKGROUND: A microscopic analysis of tissue is the gold standard for cancer detection. Hematoxylin-eosin (HE) for the reporting of prostate biopsy (PB) is conventionally based on fixation, processing, acquisition of glass slides, and analysis with a...
PURPOSE: Hierarchical clustering (HC), an unsupervised machine learning (ML) technique, was applied to multi-parametric MR (mp-MR) for prostate cancer (PCa). The aim of this study is to demonstrate HC can diagnose PCa in a straightforward interpretab...
BACKGROUND: Robot-assisted radical prostatectomy (RARP) has gained prominence since the da Vinci surgical system was introduced in 2000. RARP has now become a standard procedure for treating cases with localized prostate cancer. However, no study has...
Algorithms can improve the objectivity and efficiency of histopathologic slide analysis. In this paper, we investigated the impact of scanning systems (scanners) and cycle-GAN-based normalization on algorithm performance, by comparing different deep ...
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