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Objectives: To determine the repeatability of corneal measurements from anterior segment optical coherence tomography (AS-OCT) images using ImageJ software in healthy eyes compared with eyes with keratoconus. Methods: Anterior segment OCT images of 25 eyes from 14 healthy subjects and 25 eyes from 15 subjects with keratoconus between the ages of 20 and 80 years were evaluated. Two trained observers used ImageJ to measure the central corneal cross-sectional area and anterior and posterior corneal arc lengths. MedCalc statistical software was used to generate the intraclass correlation coefficient (ICC) and Bland-Altman plots (BAPs) for observer measurements. Results: Observer measurements of the central corneal cross-sectional area and anterior and posterior corneal arc lengths yielded an ICC .0.7. The ICC comparing the 3 parameters ranged from 0.75 to 0.84 for the control and 0.96 to 0.98 for the keratoconus group. No systematic proportional bias was detected by the BAPs. There were minimal differences between the 2 observer's measurements, with a mean of the difference of 0.3 mm 2 , 0 mm, and 0 mm, for the 3 measurements, respectively. Conclusions: This study suggests that ImageJ software is a repeatable and reliable tool in the analysis of corneal parameters from AS-OCT images among patients with keratoconus and may be applicable to AS-OCT imaging protocol development, an area of active keratoconus research.

Purpose: To assess the repeatability and reliability of semi-automated EyeMark Python program measurements compared to manual ImageJ image processing of anterior segment-optical coherence tomography (AS-OCT) structures in healthy and keratoconus eyes. Methods: Heidelberg AS-OCT was used to image 25 eyes from 14 healthy subjects and 25 eyes from 15 subjects with keratoconus between the ages of 20 and 80 years, collected prospectively, in this observational case-control study. Visual axis scan containing vertical fixation light beam was selected from the 15-line AS-OCT scan raster. Central corneal thickness (CCT), anterior corneal radius of curvature (ACRC), posterior corneal radius of curvature (PCRC), and truncated anterior vault (TAV) were measured using ImageJ software and the EyeMark Python program. MedCalc and R were used to calculate the intraclass correlation coefficient (ICC) and generate Bland-Altman plots (BAP). Results: When comparing the measurements of CCT, ACRC, PCRC, and TAV between manual ImageJ analysis and the EyeMark Python program, ICC values were consistently greater than 0.9, indicating excellent agreement. BAPs comparing the ImageJ and Python measurements of anterior segment structures show no systematic proportional bias and the average differences were near zero and within 95% of the limits of agreement. Conclusions: Semi-automated tools may provide the necessary efficiency for point-of-care quantitative corneal analysis of raw AS-OCT images. The semi-automated EyeMark Python program offers a repeatable and reliable tool compared to manual ImageJ analysis for measuring anterior segment structures from AS-OCT images among individuals with keratoconus.