Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization
This study delivers an AI-driven platform featuring a preprocessing algorithm that automates eye region cropping, correcting head tilt variations to improve image quality for AI development and clinical use. Integrated with electronic archives and patient-physician interaction, it enhances workflow efficiency, ensures telemedicine privacy, and supports ophthalmological research and strabismus care.
Authors
- Xiaohang Chen (ORCID: https://orcid.org/0000-0002-0165-3607)
- Jiaming Liu
- Dawen Wu (ORCID: https://orcid.org/0000-0002-4938-3044)
- Longqian Liu (ORCID: https://orcid.org/0000-0002-2265-4625)
- Wenyi Shang (ORCID: https://orcid.org/0000-0002-1308-8422)
- Haixian Zhang (ORCID: https://orcid.org/0000-0002-9821-508X)
- Zeyi Yang (ORCID: https://orcid.org/0009-0000-2672-4734)
- Yanfei Li (ORCID: https://orcid.org/0000-0002-7370-6763)
- Yin Teng (ORCID: https://orcid.org/0009-0003-1254-6705)
- Bin Xie (ORCID: https://orcid.org/0000-0002-5137-1640)
- Guoyuan Yang (ORCID: https://orcid.org/0000-0002-7314-836X)
Institutions
- Sichuan University (CN)
- West China Hospital of Sichuan University (CN)
- Chengdu University (CN)
Publication Details
- Journal
- Journal of Medical Internet Research
- Published
- 2025-06-03
- DOI
- https://doi.org/10.2196/74402
- Citations
- 2
- Primary Topic
- Dental Radiography and Imaging
- Type
- article
- Field-Weighted Citation Impact
- 3.58