Comparison and analysis of deep learning models for discriminating longitudinal and oblique vaginal septa based on ultrasound imaging
Convolutional neural network-based model (ConvNeXt-B) shows promising capability of discriminating longitudinal and oblique vaginal septa ultrasound images and is expected to be introduced to clinical ultrasonographic diagnostic system.
Authors
- Xiangyi Ma (ORCID: https://orcid.org/0000-0003-3414-6158)
- Jingfang Li (ORCID: https://orcid.org/0000-0002-7674-516X)
- Xin Hou
- Jin Li (ORCID: https://orcid.org/0000-0003-0610-2991)
- Liang Wang (ORCID: https://orcid.org/0000-0001-5224-8647)
- Xiangyu Wang (ORCID: https://orcid.org/0000-0001-8110-0297)
Institutions
- Tongji Hospital (CN)
- Union Hospital (CN)
- Huazhong University of Science and Technology (CN)
Publication Details
- Journal
- BMC Medical Imaging
- Published
- 2024-12-23
- DOI
- https://doi.org/10.1186/s12880-024-01507-x
- Primary Topic
- Pelvic floor disorders treatments
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Key Research and Development Program of China