Deep learning-based image analysis of eyelid morphology in thyroid-associated ophthalmopathy.

ABSTRACT:

Background

We aimed to propose a deep learning-based approach to automatically measure eyelid morphology in patients with thyroid-associated ophthalmopathy (TAO).

Methods

This prospective study consecutively included 74 eyes of patients with TAO and 74 eyes of healthy volunteers visiting the ophthalmology department in a tertiary hospital. Patients diagnosed as TAO and healthy volunteers who were age- and gender-matched met the eligibility criteria for recruitment. Facial images were taken under the same light conditions. Comprehensive eyelid morphological parameters, such as palpebral fissure (PF) length, margin reflex distance (MRD), eyelid retraction distance, eyelid length, scleral area, and mid-pupil lid distance (MPLD), were automatically calculated using our deep lear

SUBMITTER: Shao J 

PROVIDER: S-EPMC10006102 | biostudies-literature | 2023 Mar

REPOSITORIES: biostudies-literature