Deep learning-based image analysis for automated measurement of eyelid morphology before and after blepharoptosis surgery.

ABSTRACT:

Background and aim

Eyelid position and contour abnormality could lead to various diseases, such as blepharoptosis, which is a common eyelid disease. Accurate assessment of eyelid morphology is important in the management of blepharoptosis. We aimed to proposed a novel deep learning-based image analysis to automatically measure eyelid morphological properties before and after blepharoptosis surgery.

Methods

This study included 135 ptotic eyes of 103 patients who underwent blepharoptosis surgery. Facial photographs were taken preoperatively and postoperatively. Margin reflex distance (MRD) 1 and 2 of the operated eyes were manually measured by a senior surgeon. Multiple eyelid morphological parameters, such as MRD1, MRD2, upper eyelid length and corneal area, were automaticall

SUBMITTER: Lou L 

PROVIDER: S-EPMC8805858 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature