TATHAM A.

We present a deep learning semantic segmentation algorithm for processing images acquired by a novel ophthalmic device, the NIDEK GS-1. The proposed model can sophisticate the current reference exam, called gonioscopy, for evaluating the risk of developing glaucoma, a severe eye pathology with a considerable worldwide impact in terms of costs...

To develop and test a deep learning (DL) model for semantic segmentation of anatomical layers of the anterior chamber angle (ACA) in digital gonio-photographs. We used a pilot dataset of 274 ACA sector images, annotated by expert ophthalmologists to delineate five anatomical layers: iris root, ciliary body band, scleral spur, trabecular...

Purpose: To quantitatively evaluate the inter-annotator variability of clinicians tracing the contours of anatomical layers of the iridocorneal angle on digital gonio photographs, thus providing a baseline for the validation of automated analysis algorithms. Methods: Using a software annotation tool on a common set of 20 images, five...