CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation
Abstract
Accurate segmentation of the prostate and organs at risk (e.g., bladder and rectum) in CT images is a crucial step for radiation therapy in the treatment of prostate cancer. However, it is a very challenging task due to unclear boundaries, large intra- and inter-patient shape variability, and uncertain existence of bowel gases and fiducial markers. In this paper, we propose a novel automatic segmentation framework using fully convolutional...
Paper Details
Title
CT male pelvic organ segmentation using fully convolutional networks with boundary sensitive representation
Published Date
May 1, 2019
Journal
Volume
54
Pages
168 - 178
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