Computer-Aided Glaucoma Diagnosis System
Computer-Aided Glaucoma Diagnosis System

Author: Arwa Ahmed Gasm Elseid

Publisher: CRC Press

Published: 2020-05-14

Total Pages: 173

ISBN-13: 1000070050

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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.

Efficient Computer-Aided Techniques to Detect Glaucoma
Efficient Computer-Aided Techniques to Detect Glaucoma

Author: Nataraj Vijapur

Publisher:

Published: 2018

Total Pages: 0

ISBN-13:

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A survey of the World Health Organization has revealed that retinal eye disease Glaucoma is the second leading cause for blindness worldwide. It is a disease which will steals the vision of the patient without any warning or symptoms. About half of the World Glaucoma Patients are estimated to be in Asia. Hence, for social and economic reasons, Glaucoma detection is necessary in preventing blindness and reducing the cost of surgical treatment of the disease. The objective of the chapter is to predict and detect Glaucoma efficiently using image processing techniques. We have developed an efficient computer-aided Glaucoma detection system to classify a fundus image as either normal or glaucomatous image based on the structural features of the fundus image such as cup-to-disc ratio (CDR), rim-to-disc ratio (RDR), superior and inferior neuroretinal rim thicknesses, vessel structure-based features, and distribution of texture features in the fundus images. An automated clinical support system is developed to assist the ophthalmologists to identify the persons who are at risk in the early stages of the disease, monitor the progression of the disease, and minimize the examination time.

Advances in Machine Learning and Data Science
Advances in Machine Learning and Data Science

Author: Damodar Reddy Edla

Publisher: Springer

Published: 2018-05-16

Total Pages: 383

ISBN-13: 9811085692

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The Volume of “Advances in Machine Learning and Data Science - Recent Achievements and Research Directives” constitutes the proceedings of First International Conference on Latest Advances in Machine Learning and Data Science (LAMDA 2017). The 37 regular papers presented in this volume were carefully reviewed and selected from 123 submissions. These days we find many computer programs that exhibit various useful learning methods and commercial applications. Goal of machine learning is to develop computer programs that can learn from experience. Machine learning involves knowledge from various disciplines like, statistics, information theory, artificial intelligence, computational complexity, cognitive science and biology. For problems like handwriting recognition, algorithms that are based on machine learning out perform all other approaches. Both machine learning and data science are interrelated. Data science is an umbrella term to be used for techniques that clean data and extract useful information from data. In field of data science, machine learning algorithms are used frequently to identify valuable knowledge from commercial databases containing records of different industries, financial transactions, medical records, etc. The main objective of this book is to provide an overview on latest advancements in the field of machine learning and data science, with solutions to problems in field of image, video, data and graph processing, pattern recognition, data structuring, data clustering, pattern mining, association rule based approaches, feature extraction techniques, neural networks, bio inspired learning and various machine learning algorithms.

Visual Impairment and Blindness
Visual Impairment and Blindness

Author: Giuseppe Lo Giudice

Publisher: BoD – Books on Demand

Published: 2020-09-09

Total Pages: 398

ISBN-13: 1838802576

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Blindness and vision impairment affect at least 2.2 billion people worldwide with most individuals having a preventable vision impairment. The majority of people with vision impairment are older than 50 years, however, vision loss can affect people of all ages. Reduced eyesight can have major and long-lasting effects on all aspects of life, including daily personal activities, interacting with the community, school and work opportunities, and the ability to access public services. This book provides an overview of the effects of blindness and visual impairment in the context of the most common causes of blindness in older adults as well as children, including retinal disorders, cataracts, glaucoma, and macular or corneal degeneration.

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning
Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

Author: Rani, Geeta

Publisher: IGI Global

Published: 2020-10-16

Total Pages: 586

ISBN-13: 1799827437

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By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.

Automated Diagnosis of Glaucoma Using Ai Techniques
Automated Diagnosis of Glaucoma Using Ai Techniques

Author: Ahmed Salah Ghorab

Publisher: LAP Lambert Academic Publishing

Published: 2011-08

Total Pages: 132

ISBN-13: 9783845428215

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Glaucoma is a major cause of blindness globally. It damages the optic nerve cells that transmit visual information to the brain. Intra-Ocular Pressure (IOP) is the most significant danger reason to develop glaucoma. Even though a number of variables, including various optic disc parameters, have been used to discover early glaucoma damage, there is a real need for computer-aided detection (CAD) methods that can identify early glaucomatous development so that treatment to avoid further progression can be started especially in mass screenings, because ophthalmologists have limited time to assess mass number of fundus images.This thesis focused on the description of a system based on image processing and classification techniques for the estimation of quantitative parameters to classify fundus images into two classes: glaucoma patients and normal patients.

Computer-Aided Diagnosis of Glaucoma using Morphological Filters and Machine Learning
Computer-Aided Diagnosis of Glaucoma using Morphological Filters and Machine Learning

Author: Vikrant Bhateja

Publisher: Academic Press

Published: 2023-05-01

Total Pages: 0

ISBN-13: 9780323954129

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Computer-Aided Diagnosis of Glaucoma using Morphological Filters and Machine Learning provides a focused research-based case-study of CAD of glaucoma using advanced image processing and machine learning algorithms. The book discusses relevant, state-of-the-art solutions and existing challenges, along with the steps needed to develop a CAD methodology as a projected solution. Different cases of vision disorders specific to Glaucoma are presented with results evaluated by various image quality assessment metrics and opinions from medical practitioners.

Artificial Intelligence in Ophthalmology
Artificial Intelligence in Ophthalmology

Author: Andrzej Grzybowski

Publisher: Springer Nature

Published: 2021-10-13

Total Pages: 280

ISBN-13: 3030786013

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This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.

Diabetes and Fundus OCT
Diabetes and Fundus OCT

Author: Ayman S. El-Baz

Publisher: Elsevier

Published: 2020-04-17

Total Pages: 434

ISBN-13: 0128174404

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Diabetes and Fundus OCT brings together a stellar cast of authors who review the computer-aided diagnostic (CAD) systems developed to diagnose non-proliferative diabetic retinopathy in an automated fashion using Fundus and OCTA images. Academic researchers, bioengineers, new investigators and students interested in diabetes and retinopathy need an authoritative reference to bring this multidisciplinary field together to help reduce the amount of time spent on source-searching and instead focus on actual research and the clinical application. This reference depicts the current clinical understanding of diabetic retinopathy, along with the many scientific advances in understanding this condition. As the role of optical coherence tomography (OCT) in the assessment and management of diabetic retinopathy has become significant in understanding the vireo retinal relationships and the internal architecture of the retina, this information is more critical than ever. Includes unique information for academic clinicians, researchers and bioengineers Provides insights needed to understand the imaging modalities involved, the unmet clinical need that is being addressed, and the engineering and technical approaches applied Brings together details on the retinal vasculature in diabetics as imaged by optical coherence tomography angiography and automated detection of retinal disease