Recommendation on data collection and annotation of ocular appearance images in ptosis

Abstract

Ptosis is a common ophthalmologic condition, and the diagnosis is primarily based on ocular appearance. The diagnosis of such conditions can be improved using emerging technology such as artificial intelligence-based methods. However, unified data collection and labeling standards have not yet been established. This directly impacts the accuracy of ptosis diagnosis based on appearance alone. Therefore, in the present study, we aimed to establish a procedure to obtain and label images to devise a recommendation system for optimal recognition of ptosis based on ocular appearances. This would help to standardize and facilitate data sharing and serve as a guideline for the development and improvisation of algorithms in artificial intelligence for ptosis.