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We propose a 3D prostate segmentation method for transrectal ultrasound (TRUS) images, which is based on patch-based feature learning framework.
Mar 21, 2016 · We propose a 3D prostate segmentation method for transrectal ultrasound (TRUS) images, which is based on patch-based feature learning framework.
PDF | We propose a 3D prostate segmentation method for transrectal ultrasound (TRUS) images, which is based on patch-based feature learning framework.
A new prostate segmentation approach based on the optimal feature learning framework is developed, demonstrated its clinical feasibility, and validated its ...
Mar 21, 2016 · We propose a 3D prostate segmentation method for transrectal ultrasound (TRUS) images, which is based on patch-based feature learning ...
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Mar 3, 2024 · Liu, “3D transrectal ultrasound (TRUS) prostate segmentation based on optimal feature learning framework,” in Medical Imaging 2016: Image ...
A 3D segmentation method based on longitudinal image registration and machine learning is developed for transrectal ultrasound (TRUS) images, ...
Jun 29, 2015 · We have developed a new prostate segmentation approach based on the optimal feature learning framework, demonstrated its clinical ...
PDF | We developed a three-dimensional (3D) segmentation method for transrectal ultrasound (TRUS) images, which is based on longitudinal image.
May 10, 2019 · We developed a novel deeply supervised deep learning-based approach with reliable contour refinement to automatically segment the TRUS prostate, ...