Computer-Aided Glaucoma Diagnosis System - Gasm Elseid, Arwa Ahmed

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Auteur(s) : Gasm Elseid, Arwa Ahmed - Mohammed Hamza, Alnazier Osman

Editeur : Taylor & Francis Ltd

Langue : Anglais

Parution : 01/06/2020

Format : Moyen, de 350g à 1kg

Nombre de pages : 154

Expédition : 476

ISBN : 9780367406264

Résumé :
1. Introduction- Computer Aided Diagnosis. 2. Medical Background-Glaucoma Diagnosis. 3. Related Works-OD and OC Segmentation, Disc to Cup Ratio (CDR). 4. Research Methodology-Fundus Image Datasets, Image Preprocessing and Enhancement 5. Results and Discussions-Image Preparation, Feature Extraction, Classification . 6. Conclusion and Future Scope....

Biographie:

Dr. Arwa Ahmed Gasm Elseid is an Assistant Professor in Biomedical Engineering, Khartoum, Sudan. Her research has centered on CAD (Computer Aided Diagnosing) system for Glaucoma detection via digital fundus image, which developed a new algorithm used image processing techniques (contrast equalization, filtration, edge detection and segmentation, feature extraction and selection) then classification the analyzed data from feature extracted. A critical aspect of this work has lead to the development of accurate and inexpensive CAD system for glaucoma diagnosing using matlab software.

Dr. Alnazier Osman Mohammed Hamza is Professor of Medical Imaging, College of Engineering, Sudan University of Sciences and Technology, Khartoum, Sudan. He is married and has six children.

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Sommaire:

Glaucoma is the second leading cause of blindness globally. Early detection and treatment can prevent its progression to avoid total blindness. This book discusses and reviews current approaches for detection and examines new approaches for diagnosing glaucoma using CAD system.

Computer-Aided Glaucoma Diagnosis System, Chapter 1 provides a brief introduction of the disease and current methodology used to diagnose it today. Chapter 2 presents a review of the medical background of the disease, followed by a theoretical and mathematical background used in fundus image processing. Chapter 3 is a literature review about segmentation and feature extraction. Chapter 4 describes the formulation of the proposed methodology. In Chapter 5, the results of optic disc and optic cup segmentation algorithm are presented, the feature extraction and selection method, experimental results and performance evaluations of the classifier are given. Chapter 6 presents the conclusions and discussion of the future potential for the diagnostic system.

This book is intended for biomedical engineers, computer science students, ophthalmologists and radiologists looking to develop a reliable automated computer-aided diagnosis system (CAD) for detecting glaucoma and improve diagnosis of the disease.

Key Features

• Discusses a reliable automated computer-aided diagnosis system (CAD) for detecting glaucoma and presents an algorithm that detects optic disc and optic cup
• Assists ophthalmologists and researchers to test a new diagnostic method that reduces the effort and time of the doctors and cost to the patients
• Discusses techniques to reduce human error and minimize the miss detection rate and facilitate early diagnosis and treatment
• Presents algorithms to detect cup and disc color, shape features and RNFL texture features

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

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