The Devil Is in the Boundary: Boundary-Enhanced Polyp Segmentation-Reference-Cited by-同舟云学术

The Devil Is in the Boundary: Boundary-Enhanced Polyp Segmentation

Published:2024-07 Issue:7 Volume:34 Page:5414-5423
ISSN:1051-8215
Container-title:IEEE Transactions on Circuits and Systems for Video Technology
language:
Short-container-title:IEEE Trans. Circuits Syst. Video Technol.

Author:

Liu Zhizhe¹^ORCID,Zheng Shuai¹^ORCID,Sun Xiaoyi¹,Zhu Zhenfeng¹^ORCID,Zhao Yawei²^ORCID,Yang Xuebing³^ORCID,Zhao Yao¹^ORCID

Affiliation:

1. Beijing Key Laboratory of Advanced Information Science and Network Technology and the Institute of Information Science, Beijing Jiaotong University, Beijing, China

2. Medical Big Data Research Center, Chinese PLA General Hospital, Beijing, China

3. State Key Laboratory of Multimodal Artificial Intelligence Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China

Funder

Science and Technology Innovation 2030—New Generation Artificial Intelligence Major Project

National Natural Science Foundation of China

Beijing Natural Science Foundation

National High Level Hospital Clinical Research Funding

Artificial Intelligence Public Service Platform for Screening and Auxiliary Diagnosis of Medical and Health Conditions

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/76/10582818/10378660.pdf?arnumber=10378660

Reference48 articles.

1. Lesion-Aware Dynamic Kernel for Polyp Segmentation

2. Colorectal cancer statistics, 2020

3. Real-time automatic polyp detection in colonoscopy using feature enhancement module and spatiotemporal similarity correlation unit

4. A self-attention based faster R-CNN for polyp detection from colonoscopy images

5. Automated polyp segmentation in colonoscopy images via deep network with lesion-aware feature selection and refinement