This paper is in the following e-collection/theme issue:

Artificial Intelligence (2192) Ophthalmology (70) Machine Learning (2124) Tools, Programs and Algorithms (385) Assistive Technology for Vision Loss/Impairment (25)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/74402, first published .
Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization

Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization

Deep Learning–Based Precision Cropping of Eye Regions in Strabismus Photographs: Algorithm Development and Validation Study for Workflow Optimization

Authors of this article:

Dawen Wu1 Author Orcid Image ;   Yanfei Li2 Author Orcid Image ;   Zeyi Yang1 Author Orcid Image ;   Teng Yin2 Author Orcid Image ;   Xiaohang Chen1 Author Orcid Image ;   Jingyu Liu2 Author Orcid Image ;   Wenyi Shang2 Author Orcid Image ;   Bin Xie1 Author Orcid Image ;   Guoyuan Yang1 Author Orcid Image ;   Haixian Zhang2 Author Orcid Image ;   Longqian Liu1 Author Orcid Image
Article Authors Cited by (2) Tweetations Metrics

Journals

  1. Shin H, Kim S, Park S, Kim M, Kang H. Artificial Intelligence for Diagnosing Cranial Nerve III, IV, and VI Palsies Using Nine-Directional Ocular Photographs. Applied Sciences 2025;15(20):11174 View
  2. Baytaroğlu A, Çiftci Ş. Pilot Validation of ChatGPT-Based Strabismus Assessment Using 9Gaze Photographs: A Single-Center Feasibility Study. Ege Tıp Bilimleri Dergisi 2025;8(3):155 View