Asymmetrical Multi-task Attention U-Net for the Segmentation of Prostate Bed in CT Image.

ABSTRACT: Segmentation of the prostate bed, the residual tissue after the removal of the prostate gland, is an essential prerequisite for post-prostatectomy radiotherapy but also a challenging task due to its non-contrast boundaries and highly variable shapes relying on neighboring organs. In this work, we propose a novel deep learning-based method to automatically segment this "invisible target". As the main idea of our design, we expect to get reference from the surrounding normal structures (bladder&rectum) and take advantage of this information to facilitate the prostate bed segmentation. To achieve this goal, we first use a U-Net as the backbone network to perform the bladder&rectum segmentation, which serves as a low-level task that can provide references to the high-level task of the prostate

SUBMITTER: Xu X 

PROVIDER: S-EPMC8221064 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature