Abstract
Glaucoma is a leading eye disease, causing vision loss by gradually affecting peripheral vision if left untreated. Current diagnosis of glaucoma is performed by ophthalmologists, human experts who typically need to analyze different types of medical images generated by different types of medical equipment: fundus, Retinal Nerve Fiber Layer (RNFL), Optical Coherence Tomography (OCT) disc, OCT macula, perimetry, and/or perimetry deviation. Capturing and analyzing these medical images is labor intensive and time consuming. In this paper, we present a novel approach for glaucoma diagnosis and localization, only relying on fundus images that are analyzed by making use of state-of-the-art deep learning techniques. Specifically, our approach towards glaucoma diagnosis and localization leverages Convolutional Neural Networks (CNNs) and Gradient-weighted Class Activation Mapping (Grad-CAM), respectively. We built and evaluated different predictive models using a large set of fundus images, collected and labeled by ophthalmologists at Samsung Medical Center (SMC). Our experimental results demonstrate that our most effective predictive model is able to achieve a high diagnosis accuracy of 96%, as well as a high sensitivity of 96% and a high specificity of 100% for Dataset-Optic Disc (OD), a set of center-cropped fundus images highlighting the optic disc. Furthermore, we present Medinoid, a publicly-available prototype web application for computer-aided diagnosis and localization of glaucoma, integrating our most effective predictive model in its back-end.
Highlights
Glaucoma is a progressive optic neuropathy [1], mostly manifesting itself in the area between the optic disc and the macula
When only considering the results presented for Dataset-Optic Disc (OD) in both Tables 5 and 6, the ResNet-152-M model was able to outperform all other models, in terms of all metrics presented
Using Grad-Class Activation Mapping (CAM), a weakly-supervised localization method, our predictive model was able to highlight where a glaucomatous area can be found in a given input image
Summary
Glaucoma is a progressive optic neuropathy [1], mostly manifesting itself in the area between the optic disc and the macula. The progress of glaucoma usually remains undetected until the optic nerve gets irreversibly damaged. The earlier glaucoma is diagnosed and treated, the less patients suffer from irreversible disease progress leading to blindness. The global prevalence of glaucoma is approximately 3–5% for people aged 40–80 years. The number of people aged 40–80 years and affected by glaucoma worldwide was estimated to be 64 million in 2013, and this number is expected to increase to 76 million in 2020 and to 112 million in
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