Noise-induced modality-specific pretext learning for pediatric chest X-ray image classification
The superior results of CXR modality-specific pretext learning and their ensemble underscore its potential as a viable alternative to conventional ImageNet pretraining for medical image classification. Results from this study promote further exploration of medical modality-specific TL techniques in the development of DL models for various medical imaging applications.
Authors
- Zhaohui Liang (ORCID: https://orcid.org/0000-0002-9361-5535)
- Sivaramakrishnan Rajaraman (ORCID: https://orcid.org/0000-0003-0871-8634)
- Zhiyun Xue (ORCID: https://orcid.org/0000-0003-0644-385X)
- Sameer Antani (ORCID: https://orcid.org/0000-0002-0040-1387)
Institutions
- National Institutes of Health (US)
- United States National Library of Medicine (US)
Publication Details
- Journal
- Frontiers in Artificial Intelligence
- Published
- 2024-09-05
- DOI
- https://doi.org/10.3389/frai.2024.1419638
- Primary Topic
- COVID-19 diagnosis using AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Institutes of Health
- U.S. National Library of Medicine