Topographic analysis of eyelid position using digital image processing software

Abstract

Purpose: To propose a novel analysis technique for objective quantification of topographic eyelid position with an algorithmatically calculated scheme and to determine its feasibility. Methods: One hundred normal eyelids from 100 patients were segmented using a graph cut algorithm, and 11 shape features of eyelids were semi-automatically quantified using in-house software. To evaluate the intra-and inter-examiner reliability of this software, intra-class correlation coefficients (ICCs) were used. To evaluate the diagnostic value of this scheme, the correlations between semiautomatic and manual measurements of margin reflex distance 1 (MRD1) and margin reflex distance 2 (MRD2) were analysed using a Bland-Altman analysis. To determine the degree of agreement according to manual MRD length, the relationship between the variance of semi-automatic measurements and the manual measurements was evaluated using linear regression. Results: Intra-and inter-examiner reliability were excellent, with ICCs ranging from 0.913 to 0.980 in 11 shape features including MRD1, MRD2, palpebral fissure, lid perimeter, upper and lower lid lengths, roundness, total area, and medial, central, and lateral areas. The correlations between semi-automatic and manual MRDs were also excellent, with better correlation in MRD1 than in MRD2 (R = 0.893 and 0.823, respectively). In addition, significant positive relationships were observed between the variance and the length of MRD1 and 2; the longer the MRD length, the more the variance. Conclusion: The proposed novel optimized integrative scheme, which is shown to have high repeatability and reproducibility, is useful for topographic analysis of eyelid position.