Computer-Aided Glaucoma Diagnosis System

Glaucoma, the second leading cause of blindness worldwide, can be prevented from progressing to total blindness through early detection and treatment. This book delves into the current approaches for detection and explores new diagnostic methods using a Computer-Aided Diagnosis (CAD) system.

Chapter 1 of Computer-Aided Glaucoma Diagnosis System provides a brief introduction to the disease and the methodologies currently employed for diagnosis. Chapter 2 offers a review of the medical background of glaucoma, along with the theoretical and mathematical foundations used in processing fundus images. Chapter 3 presents a literature review on segmentation and feature extraction techniques. Chapter 4 outlines the formulation of the proposed methodology. Chapter 5 showcases the results of the optic disc and optic cup segmentation algorithm, as well as the feature extraction and selection method. It also includes experimental results and performance evaluations of the classifier. Finally, Chapter 6 offers conclusions and discusses the future potential of the diagnostic system.

This book is targeted at biomedical engineers, computer science students, ophthalmologists, and radiologists who are interested in developing a reliable automated CAD system for detecting glaucoma and improving its diagnosis.

Key Features:

• Discusses the development of a reliable automated CAD system for detecting glaucoma, including an algorithm for optic disc and optic cup detection.
• Assists ophthalmologists and researchers in testing a new diagnostic method that reduces the effort and time required by doctors, as well as the cost for patients.
• Explores techniques to reduce human error, minimize miss detection rates, and facilitate early diagnosis and treatment.
• Presents algorithms for detecting cup and disc color, shape features, and retinal nerve fiber layer (RNFL) texture features.

Dr. Arwa Ahmed Gasm Elseid is an assistant professor in the Department of Biomedical Engineering at the Sudan University of Science and Technology, Khartoum, Sudan.

Dr. Alnazier Osman Mohammed Hamza is a professor of Medical Imaging at the College of Engineering, Sudan University of Sciences and Technology, Khartoum, Sudan.

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