Major advances in diagnostic technologies are offering unprecedented insight into the
condition of the retina and beyond ocular disease. Digital images providing millions of …

The lifestyle of modern society has changed significantly with the emergence of artificial
intelligence (AI), machine learning (ML), and deep learning (DL) technologies in recent …

Glaucoma is a chronic eye disease that leads to irreversible vision loss. The cup to disc ratio
(CDR) plays an important role in the screening and diagnosis of glaucoma. Thus, the …

We present a novel framework combining convolutional neural networks (CNN) and graph
search methods (termed as CNN-GS) for the automatic segmentation of nine layer …

We present a novel fully automated algorithm for the detection of retinal diseases via optical
coherence tomography (OCT) imaging. Our algorithm utilizes multiscale histograms of …

The Sørensen-Dice index (SDI) is a widely used measure for evaluating medical image
segmentation algorithms. It offers a standardized measure of segmentation accuracy which …

We present a fully automatic algorithm to identify fluid-filled regions and seven retinal layers
on spectral domain optical coherence tomography images of eyes with diabetic macular …

We present an image projection network (IPN), which is a novel end-to-end architecture and
can achieve 3D-to-2D image segmentation in optical coherence tomography angiography …

Given that the neural and connective tissues of the optic nerve head (ONH) exhibit complex
morphological changes with the development and progression of glaucoma, their …

We look at the recent application of deep learning (DL) methods in automated fine-grained
segmentation of spectral domain optical coherence tomography (OCT) images of the retina …