Accurate segmentation of Magnetic Resonance (MR) on prostate is an essential step for robotics surgery in prostate cancer treatment planning. This paper proposes a Hierarchical Boundary Sensitive Residual U-net (HBS-RUnet) model with self-paced learning strategy for prostate segmentation in MR image. Instead of regarding the segmentation task independently, our network consists of two branches: one segmentation branch detects the prostate region and the boundary branch finds prostate shape. The outputs of boundary branch are employed to refine the HBS-RUnet model by adding a boundary regularization, which helps to lind desirable and spatially consistent prostate region. Moreover, a hierarchical dynamic self-paced learning strategy is proposed to measure the difficulty for each prostate image and gradually select the relatively simpler samples for model training. Such a simple-to-complex learning strategy could robustly lean: image features and enable the robust prostate segmentation. We applied 66 cases from the PROSTATEx Challenge to evaluate the robustness and effectiveness of the proposed HBS-RUnet, and our fully automatic segmentation results demonstrate high consistency (DSC 87.1%) with the manual segmentation results by experienced physicians.
基金:
Shenzhen-Hong Kong Innovation Circle Category D Project [SGDX2019081623300177, 9240008]; Shenzhen basic technology research project [JCYJ20170818160306270]
语种:
外文
被引次数:
WOS:
第一作者:
第一作者机构:[1]Chinese Acad Sci, Shenzhen Inst Adv Technol, Shenzhen, Guangdong, Peoples R China
推荐引用方式(GB/T 7714):
Qin Wenjian,Xiao Zhibo,Xie Yaoqin,et al.Self-Paced Learning for Automatic Prostate Segmentation on MR Images with Hierarchical Boundary Sensitive Network[J].2020 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE-RCAR 2020).2020,321-326.doi:10.1109/RCAR49640.2020.9303035.
APA:
Qin, Wenjian,Xiao, Zhibo,Xie, Yaoqin&Yuan, Yixuan.(2020).Self-Paced Learning for Automatic Prostate Segmentation on MR Images with Hierarchical Boundary Sensitive Network.2020 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE-RCAR 2020),,
MLA:
Qin, Wenjian,et al."Self-Paced Learning for Automatic Prostate Segmentation on MR Images with Hierarchical Boundary Sensitive Network".2020 IEEE INTERNATIONAL CONFERENCE ON REAL-TIME COMPUTING AND ROBOTICS (IEEE-RCAR 2020) .(2020):321-326