AUTHOR=Bao Xiao-Li , Sun Ying-Jian , Zhan Xi , Li Guang-Yu 

TITLE=Orbital and eyelid diseases: The next breakthrough in artificial intelligence?

JOURNAL=Frontiers in Cell and Developmental Biology

VOLUME=10

YEAR=2022

URL=https://www.frontiersin.org/journals/cell-and-developmental-biology/articles/10.3389/fcell.2022.1069248

DOI=10.3389/fcell.2022.1069248

ISSN=2296-634X

ABSTRACT=<p>Orbital and eyelid disorders affect normal visual functions and facial appearance, and precise oculoplastic and reconstructive surgeries are crucial. Artificial intelligence (AI) network models exhibit a remarkable ability to analyze large sets of medical images to locate lesions. Currently, AI-based technology can automatically diagnose and grade orbital and eyelid diseases, such as thyroid-associated ophthalmopathy (TAO), as well as measure eyelid morphological parameters based on external ocular photographs to assist surgical strategies. The various types of imaging data for orbital and eyelid diseases provide a large amount of training data for network models, which might be the next breakthrough in AI-related research. This paper retrospectively summarizes different imaging data aspects addressed in AI-related research on orbital and eyelid diseases, and discusses the advantages and limitations of this research field.</p>