This book presents an automated system for the detection and analysis of common retinal diseases from fundus images. The author, Hillol Das, details approaches for identifying Diabetic Retinopathy, Retinitis Pigmentosa, and Glaucoma, conditions that can lead to irreversible vision loss if not treated early. The system utilizes image processing techniques, with experimental results demonstrating a significant detection rate, particularly in locating the optic disk using normalized cross-correlation. The proposed automated system aims to facilitate mass screening in underserved rural areas and reduce overall screening costs.

The book focuses on a technical application of image processing within medical science, specifically for ophthalmological diagnostics. The author's approach emphasizes the development of an automated system to aid in the early detection of prevalent retinal diseases like Diabetic Retinopathy, Retinitis Pigmentosa, and Glaucoma. The methodology detailed, including the use of normalized cross-correlation for optic disk detection, is presented with experimental validation to support its efficacy. The work is positioned as a tool for improving healthcare accessibility in areas with limited specialist availability and for reducing screening expenses.