TriLA: Triple-Level Alignment Based Unsupervised Domain Adaptation for Joint Segmentation of Optic Disc and Optic Cup-Reference-Cited by-同舟云学术

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TriLA: Triple-Level Alignment Based Unsupervised Domain Adaptation for Joint Segmentation of Optic Disc and Optic Cup

Published:2024-09 Issue:9 Volume:28 Page:5497-5508
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Chen Ziyang¹^ORCID,Pan Yongsheng¹^ORCID,Ye Yiwen¹^ORCID,Wang Zhiyong²^ORCID,Xia Yong¹^ORCID

Affiliation:

1. National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology, School of Computer Science and Engineering, Northwestern Polytechnical University, Xi'an, China

2. School of Computer and Science, The University of Sydney, NSW, Australia

Funder

National Natural Science Foundation of China

Key Research and Development Program of Shaanxi Province

Ningbo Clinical Research Center for Medical Imaging

Shenzhen Science and Technology Program

Innovation Foundation for Doctor Dissertation of Northwestern Polytechnical University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6221020/10666866/10540208.pdf?arnumber=10540208

Reference57 articles.

2. Ranking of optic disc variables for detection of glaucomatous optic nerve damage;Jonas;Invest. Ophthalmol. Vis. Sci.,2000

3. PKRT-Net: Prior knowledge-based relation transformer network for optic cup and disc segmentation

4. Joint Optic Disc and Cup Segmentation Based on Multi-Label Deep Network and Polar Transformation

5. PM-Net: Pyramid Multi-label Network for Joint Optic Disc and Cup Segmentation

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