Cervical OCT image classification using contrastive masked autoencoders with Swin Transformer
Our work has great potential to assist gynecologists in intelligently interpreting cervical OCT images in clinical settings. Additionally, the integrated GradCAM module of CMSwin enables cervical lesion visualization and interpretation, providing good interpretability for gynecologists to diagnose cervical diseases efficiently.
Authors
- Yuxuan Xiong (ORCID: https://orcid.org/0000-0002-7588-028X)
- Yutao Ma (ORCID: https://orcid.org/0000-0003-4239-2009)
- Qingbin Wang (ORCID: https://orcid.org/0000-0002-2415-4122)
- Xuefeng Mu
- Yan Zhang (ORCID: https://orcid.org/0000-0001-9235-6861)
- Hanfeng Zhu
Institutions
- Wuhan University (CN)
- Central China Normal University (CN)
Publication Details
- Journal
- Computerized Medical Imaging and Graphics
- Published
- 2024-11-19
- DOI
- https://doi.org/10.1016/j.compmedimag.2024.102469
- Citations
- 9
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 3.64
Funders
- Science and Technology Department of Hubei Province
- Key Research and Development Program of Hunan Province of China