Original contributionAnalysis of ultrasonographic prostate images for the detection of prostatic carcinoma: The Automated Urologic Diagnostic Expert system
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Artificial intelligence in multiparametric prostate cancer imaging with focus on deep-learning methods
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2017, Journal of Computational ScienceCitation Excerpt :Prostate ultrasound images contain high speckle noise, shadow artifacts due to calcification in prostate region, short range of gray levels and boundaries are missing especially at the base and apex region of the prostate [13], which makes the segmentation process difficult. However, ultrasound images are widely used in various computer aided diagnosis (CAD) systems [2,7–11], image guided interventions, and various therapies like brachytherapy. In localized prostate cancer, low-dose-rate (LDR) brachytherapy can be used to provide a quick and accurate diagnosis [14].
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