3D reconstruction and segmentation methods for endothelial cell count of stored corneas

Abstract

Purpose Measurement of the endothelial cell density (ECD) is the main criterion to validate the quality of corneal grafts in eye banks. Because of corneal curvature and of deep storage‐induced endothelial folds, parallax errors may result in ECD overestimation. We designed a software with 3D reconstruction and optimized segmentation methods to improve cell count reliability Methods After acquisition of endothelial Z stacks by conventional motorized bright field microscopy, a depth map was obtained by researching maximized measurements of the focus in images (shape‐from‐focus method). Texture of the surface was built by summing image parts presenting the right focus leadind to an all‐in‐focus image. By calculating first derivative in all directions of depth map, precise estimation of cells in folds surfaces could be found. In order to improve and facilitate the cell count, a segmentation method based on watershed technique was applied on the texture image. Taking account of the new 3D area, a precise corrected ECD (cECD) could be calculated. We validated the cECD by comparison with ECD obtained manually by an expert. Two types of images were used: the Keratotest (cells boundaries engraved on a quartz wafer) and real endothelial images. Two parameters were compared: quality of cells borders recognition (correct shapes) and ECD. Results Comparison results showed the relevance of these algorithms for both criteria. Automation of processing allowed gain of time compared to manual estimation Conclusion 3D endothelial count can be useful to improve corneas selection in eye banks. Grant: ANR2012 CORIMMO3D