A semantic segmentation-based automatic pterygium assessment and grading system
The AI-based diagnostic method proposed in this study achieves automatic grading of pterygium by integrating semantic segmentation and curve fitting technology, which is highly consistent with the clinical evaluation of doctors. The quantitative evaluation framework established in this study is expected to meet multiple clinical needs beyond basic diagnosis. The construction of the data set should continue to be optimized in future studies.
Authors
- Qingbo Ji (ORCID: https://orcid.org/0000-0002-3973-3434)
- Lin Zhang (ORCID: https://orcid.org/0009-0006-5293-9169)
- Wanyang Liu (ORCID: https://orcid.org/0000-0002-9959-8377)
- Hui He (ORCID: https://orcid.org/0000-0003-3348-3152)
- Qingfeng Ma (ORCID: https://orcid.org/0000-0002-0114-6402)
- Lijun Qu (ORCID: https://orcid.org/0000-0002-7519-3121)
Institutions
- Harbin Engineering University (CN)
- Harbin Medical University (CN)
- Second Affiliated Hospital of Harbin Medical University (CN)
- Ministry of Industry and Information Technology (CN)
Publication Details
- Journal
- Frontiers in Medicine
- Published
- 2025-03-13
- DOI
- https://doi.org/10.3389/fmed.2025.1507226
- Citations
- 1
- Primary Topic
- Retinal Imaging and Analysis
- Type
- article
- Field-Weighted Citation Impact
- 1.36