Segmentation of Corneal Endothelial Cells Contour by Means of a Genetic Algorithm
Corneal images acquired by in-vivo microscopy provide clinical information on the cornea endothelium health state. The reliable estimation of the clinical morphometric parameters requires the accurate detection of cell contours in a large number of cells. Thus for the practical application of this analysis in clinical settings an automated method is needed. We propose the automatic segmentation of corneal endothelial cells contour through an innovative technique based on a genetic algorithm, which combines information about the typical regularity of endothelial cells shape with the pixels intensity of the actual image. Ground truth values for the clinical parameters were obtained from manually drawn cell contours. Results show that an accurate automatic estimation is achieved: for each parameter, the mean difference between its manual estimation and the automated one is always less than 4%, and the maximum difference is always less than 7%.
Keywords: Corneal images, image segmentation, confocal microscopy
How to Cite:
Scarpa, F. & Ruggeri, A., (2015) “Segmentation of Corneal Endothelial Cells Contour by Means of a Genetic Algorithm”, Proceedings of the Ophthalmic Medical Image Analysis International Workshop 2(2015), 25-32. doi: https://doi.org/10.17077/omia.1023
Rights: Copyright © 2015 Fabio Scarpa and Alfredo Ruggeri