PURPOSE: We aimed at developing simulation software capable of producing images of corneal endothelium close to identical to images captured by clinical specular microscopy with defined morphometrical characteristics. It was further planned to demonstrate the usefulness of the simulator by analysing measurement errors associated with a trained operator using a commercially available semi-automatic algorithm for analysis of simulated images. METHODS: Software was developed that allows creation of unique images of the corneal endothelium expressing morphology close to identical with that seen in images of corneal specular microscopy. Several hundred unique images of the corneal endothelium were generated with randomization, spanning a physiological range of endothelial cell density. As an example of the usefulness of the simulator for analysis of measurement errors in corneal specular microscopy, a total of 12 of all the images generated were randomly selected such that the endothelial cell density expressed was evenly distributed over the physiological range of endothelial cell density. The images were transferred to a personal computer. The imagenet-640 software was used to analyse endothelial cell size variation, percentage of hexagonal endothelial cells, and endothelial cell density. RESULTS: The simulator developed allows randomized generation of corneal specular microscopy images with a preset expected average and variation of cell structure. Calculated morphometric information of each cell is stored in the simulator. The image quality can secondarily be varied with a toolbox of filters to approximate a large spectrum of clinically captured images. As an example of the use of the simulator, measurement errors associated with one trained operator using the imagenet-640 software, and focusing on endothelial cell density, were examined. The functional dependence between morphometric information estimated with the imagenet-640 software algorithm and real morphometric information as provided by the simulator was analysed with regression. It was demonstrated that that the estimations of endothelial cell size variation was associated with a scaling error and that the random error was strongly dependent on the operator. CONCLUSION: The newly developed simulator for randomized generation of morphometrically defined corneal specular microscopy images for the first time makes it possible to estimate a spatial scaling error of an available semi-automatic algorithm and to determine the random measurement error of important morphometric estimates in a defined reference sample of images. It is anticipated that the simulator will be a valuable tool for the generation of a large set of morphometrically well-characterized corneal specular microscopy images that can be used for calibration among research centres, for minimization of random errors and for measurement of quality control. Simulated images will be useful for the development of fully automatic analysis of corneal endothelial cell morphometry.
PURPOSE: We aimed at developing simulation software capable of producing images of corneal endothelium close to identical to images captured by clinical specular microscopy with defined morphometrical characteristics. It was further planned to demonstrate the usefulness of the simulator by analysing measurement errors associated with a trained operator using a commercially available semi-automatic algorithm for analysis of simulated images. METHODS: Software was developed that allows creation of unique images of the corneal endothelium expressing morphology close to identical with that seen in images of corneal specular microscopy. Several hundred unique images of the corneal endothelium were generated with randomization, spanning a physiological range of endothelial cell density. As an example of the usefulness of the simulator for analysis of measurement errors in corneal specular microscopy, a total of 12 of all the images generated were randomly selected such that the endothelial cell density expressed was evenly distributed over the physiological range of endothelial cell density. The images were transferred to a personal computer. The imagenet-640 software was used to analyse endothelial cell size variation, percentage of hexagonal endothelial cells, and endothelial cell density. RESULTS: The simulator developed allows randomized generation of corneal specular microscopy images with a preset expected average and variation of cell structure. Calculated morphometric information of each cell is stored in the simulator. The image quality can secondarily be varied with a toolbox of filters to approximate a large spectrum of clinically captured images. As an example of the use of the simulator, measurement errors associated with one trained operator using the imagenet-640 software, and focusing on endothelial cell density, were examined. The functional dependence between morphometric information estimated with the imagenet-640 software algorithm and real morphometric information as provided by the simulator was analysed with regression. It was demonstrated that that the estimations of endothelial cell size variation was associated with a scaling error and that the random error was strongly dependent on the operator. CONCLUSION: The newly developed simulator for randomized generation of morphometrically defined corneal specular microscopy images for the first time makes it possible to estimate a spatial scaling error of an available semi-automatic algorithm and to determine the random measurement error of important morphometric estimates in a defined reference sample of images. It is anticipated that the simulator will be a valuable tool for the generation of a large set of morphometrically well-characterized corneal specular microscopy images that can be used for calibration among research centres, for minimization of random errors and for measurement of quality control. Simulated images will be useful for the development of fully automatic analysis of corneal endothelial cell morphometry.