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Purpose: In vivo confocal microscopy (IVCM) is a non-invasive imaging tool that allows visualization of corneal layers at a cellular level. It provides valuable information about immune dendritiform cells (DCs) that aid with the diagnosis of a variety of inflammatory corneal pathologies. Currently analyses of these images require manual image selection. The purpose of this study is to show utilization of a deep learning system (U-Net convolutional neural network (CNN)) for classification of corneal layer images as well as DC detection and segmentation, therefore increasing diagnostic accuracy

Methods: Classification CNN was trained on 1540 images consisting of 178 endothelial layer, 441 epithelial layer, 510 subbasal nerve layer and 411 stromal keratocyte images. The method was tested on a total of 610 images comprising of 100 endothelial layer, 99 epithelial layer, 281 subbasal nerves layer and 130 stromal …