Deep Generative Adversarial Reinforcement Learning for Semi-Supervised Segmentation of Low-Contrast and Small Objects in Medical Images-Reference-Cited by-同舟云学术

Deep Generative Adversarial Reinforcement Learning for Semi-Supervised Segmentation of Low-Contrast and Small Objects in Medical Images

Published:2024-09 Issue:9 Volume:43 Page:3072-3084
ISSN:0278-0062
Container-title:IEEE Transactions on Medical Imaging
language:
Short-container-title:IEEE Trans. Med. Imaging

Author:

Xu Chenchu¹^ORCID,Zhang Tong²,Zhang Dong³^ORCID,Zhang Dingwen⁴^ORCID,Han Junwei⁴^ORCID

Affiliation:

1. School of Computer Science and Technology, Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education, Anhui University, Hefei, China

2. School of Computer Science and Technology, Anhui University, Hefei, China

3. Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada

4. Institute of Artificial Intelligence, Hefei Comprehensive National Science Center, Hefei, China

Funder

National Natural Science Foundation of China

University Synergy Innovation Program of Anhui Province

Anhui Provincial Natural Science Foundation

Institute of Artificial Intelligence, Hefei Comprehensive National Science Center

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/42/10663877/10486949.pdf?arnumber=10486949

Reference56 articles.

1. Weakly-Supervised teacher-Student network for liver tumor segmentation from non-enhanced images

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5. Uncertainty-Aware Self-ensembling Model for Semi-supervised 3D Left Atrium Segmentation

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