Automatic Measurement and Comparison of Normal Eyelid Contour by Age and Gender Using Image-Based Deep Learning

PurposeThis study aimed to propose a fully automatic eyelid measurement system and compare the contours of both the upper and lower eyelids of normal individuals according to age and gender.DesignProspective study.ParticipantsFive hundred and forty healthy Chinese from 0 to 79 years old in a tertiary hospital were included.MethodsFacial images in the primary gazing position were used to train and test the proposed automatic system for eye recognition and eye segmentation. According to the 10-millimeter diameter circular marker, measurements were transformed from pixel sizes into real-world distances.Main Outcome MeasuresMid-pupil lid distances (MPLDs) every 15 degrees of all participants were automatically measured in both genders (30 males and 30 females in each age group) by the proposed deep learning-based system. Intraclass correlation coefficients (ICCs) were performed to assess the agreement between the automatic and manual margin reflex distances (MRDs). The eyelid contour, eyelid asymmetry, and palpebral fissure obliquity were analyzed using MPLD, temporal-versus-nasal MPLD ratio, and the angle between the inner and outer canthi, respectively.ResultsThe measurement of MRDs by the automatic system excellently agreed with that of the expert, with ICCs ranging from 0.863 to 0.886. When getting older, the values of MPLDs reached the peak in the 20s or 30s and then gradually decreased at all angles. The temporal sector showed greater changes in MPLDs than the nasal sector, and the changes were more significant in females than in males. The maximum value of palpebral fissure obliquity appeared before 10 years old in both genders and maintained relatively stable after the 20s (P > 0.05).ConclusionsThe proposed deep learning-based eyelid analysis system allowed automatic, accurate, and comprehensive measurement of the eyelid contour. The refinement of eyelid shape quantification could be beneficial for future objective assessment pre and post ocular plastic surgery.