Stochastic Augmented-Based Dual-Teaching for Semi-Supervised Medical Image Segmentation
Existing semi-supervised medical image segmentation algorithms use copy-paste data augmentation to correct the labeled-unlabeled data distribution mismatch. However, current copy-paste methods have three limitations: (1) trai... | Find, read and cite all the research you need on Tech Science Press
Authors
- Hengyang Liu (ORCID: https://orcid.org/0000-0001-7825-0091)
- Pengcheng Ren (ORCID: https://orcid.org/0000-0002-3219-8125)
- Fen Luo (ORCID: https://orcid.org/0000-0001-8029-7905)
- Chengyun Song (ORCID: https://orcid.org/0000-0002-2027-4258)
- Yang Yuan (ORCID: https://orcid.org/0000-0002-0715-987X)
Publication Details
- Journal
- Computers, materials & continua/Computers, materials & continua (Print)
- Published
- 2024-11-13
- DOI
- https://doi.org/10.32604/cmc.2024.056478
- Citations
- 1
- Primary Topic
- Medical Image Segmentation Techniques
- Type
- article
- Field-Weighted Citation Impact
- 0.25
Funders
- National Natural Science Foundation of China