Entropy-driven Adversarial Training For Source-free Medical Image Segmentation-Reference-Cited by-同舟云学术

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Entropy-driven Adversarial Training For Source-free Medical Image Segmentation

Published:2023-07-24 Issue: Volume: Page:
ISSN:
Container-title:2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
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Author:

Liqiang Yuan¹,Erdt Marius²,Wang Lipo¹,Siyal Mohammed Yakoob¹,Cui Jian³

Affiliation:

1. Nanyang Technological University,School of Electical and Electronic Engineerirng,Singapore,639798

2. Nanyang Technological University,Fraunhofer Singapore,Singapore,639798

3. Zhejiang Lab,Research Center for Augmented Intelligence, Research Institute of Artificial Intelligence,Hangzhou,China,311121

Funder

National Natural Science Foundation of China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10339936/10339939/10341033.pdf?arnumber=10341033

Reference36 articles.

1. High-level prior-based loss functions for medical image segmentation: A survey

2. An Annotation Sparsification Strategy for 3D Medical Image Segmentation via Representative Selection and Self-Training

3. Automated interpretation of congenital heart disease from multi-view echocardiograms

4. Transfer Learning for Domain Adaptation in MRI: Application in Brain Lesion Segmentation

5. Subtype-aware Unsupervised Domain Adaptation for Medical Diagnosis

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