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EN
The number and shape of cells in endothelium layer is highly correlated with the quality of vision. Therefore, its precise and automatic description plays an important role in medicine. This work presents several aspects of image processing of endothelium layer acquired by specular microscope. The comparison of cell selection accuracy is discussed using two different approaches to solve this problem: convolution filtering methods, and snake-based method. Moreover, for verification results generated by dedicated software, supplied with the microscope, were utilized. Next, the precise segmentation method is applied to improve the segmentation. The results are inspected visually, but also CV, H, and CVSL parameters, used in medicine, are calculated. The research concludes that general visual outcomes achieved by all segmentation approaches give similar results, however deep insight into cell outline position reveals some differences, which were partially removed after precise segmentation application. The analysis of parameter values show high stability of CV and CVSL parameters.
EN
This article concerns the analysis of corneal endothelial image. The basic problems of binarization and segmentation of these images are discussed. Preprocessing methods are proposed, consisting of median and convolution filtration, to remove noise. An algorithm of normalization of the average brightness of the vertical and horizontal is presented. The problem of binarization is discussed. At the end the proposal of segmentation algorithm is reported.
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