PURPOSE: To use physical attributes of redness to determine the accuracy of four bulbar redness grading scales, and to cross-calibrate the scales based on these physical measures. METHODS: Two image-processing metrics, fractal dimension (D) and percentage of pixel coverage (% PC), as well as photometric chromaticity were selected as physical measures, to describe and compare grades of bulbar redness among the McMonnies/Chapman-Davies scale, the Efron Scale, the Institute for Eye Research scale, and a validated scale developed at the Centre for Contact Lens Research. Two sets of images were prepared by using image processing: The first included multiple segments covering the largest possible region of interest (ROI) within the bulbar conjunctiva in the original images; the second contained modified scale images that were matched in size and resolution across scales, and a single, equally-sized ROI. To measure photometric chromaticity, the original scale images were displayed on a computer monitor, and multiple conjunctival segments were analyzed. Pearson correlation coefficients between each set of image metrics and the reference image grades were calculated to determine the accuracy of the scales. RESULTS: Correlations were high between reference image grades and all sets of objective metrics (all Pearson's r >or= 0.88, P <or= 0.05); each physical attribute pointed to a different scale as being most accurate. Independent of the physical attribute used, there were wide discrepancies between scale grades, with almost no overlap when cross-calibrating and comparing the scales. CONCLUSIONS: Despite the generally strong linear associations between the physical characteristics of reference images in each scale, the scales themselves are not inherently accurate and are too different to allow for cross-calibration.
PURPOSE: To use physical attributes of redness to determine the accuracy of four bulbar redness grading scales, and to cross-calibrate the scales based on these physical measures. METHODS: Two image-processing metrics, fractal dimension (D) and percentage of pixel coverage (% PC), as well as photometric chromaticity were selected as physical measures, to describe and compare grades of bulbar redness among the McMonnies/Chapman-Davies scale, the Efron Scale, the Institute for Eye Research scale, and a validated scale developed at the Centre for Contact Lens Research. Two sets of images were prepared by using image processing: The first included multiple segments covering the largest possible region of interest (ROI) within the bulbar conjunctiva in the original images; the second contained modified scale images that were matched in size and resolution across scales, and a single, equally-sized ROI. To measure photometric chromaticity, the original scale images were displayed on a computer monitor, and multiple conjunctival segments were analyzed. Pearson correlation coefficients between each set of image metrics and the reference image grades were calculated to determine the accuracy of the scales. RESULTS: Correlations were high between reference image grades and all sets of objective metrics (all Pearson's r >or= 0.88, P <or= 0.05); each physical attribute pointed to a different scale as being most accurate. Independent of the physical attribute used, there were wide discrepancies between scale grades, with almost no overlap when cross-calibrating and comparing the scales. CONCLUSIONS: Despite the generally strong linear associations between the physical characteristics of reference images in each scale, the scales themselves are not inherently accurate and are too different to allow for cross-calibration.
Authors: Ilaria Macchi; Vatinee Y Bunya; Mina Massaro-Giordano; Richard A Stone; Maureen G Maguire; Yuanjie Zheng; Min Chen; James Gee; Eli Smith; Ebenezer Daniel Journal: Ocul Surf Date: 2018-06-06 Impact factor: 5.033
Authors: Ekaterina Sirazitdinova; Marlies Gijs; Christian J F Bertens; Tos T J M Berendschot; Rudy M M A Nuijts; Thomas M Deserno Journal: Transl Vis Sci Technol Date: 2019-12-12 Impact factor: 3.283