Download or read book Retinal Image Processing for Automated Detection and Grading of Diabetic Retinopathy written by Hussain Fadhel Hamdan Jaafar and published by . This book was released on 2012 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The main eye condition associated with diabetes is called diabetic retinopathy and is, the main cause of blindness. The earliest signs of this disease include damage to retinal blood vessels and then the formation of lesions such as exudates and red spots. Such lesions are normally detected manually by clinicians in intensive and time-consuming processes. Computer:--aided detection and grading of such conditions could facilitate an immediate and accurate Criagnosis. Whilst some progress has been made to detect these diseases, there is no complete system for automated detection and grading of diabetic retinopathy and this is hindering the development of automated methods to support assessment of diabetic eye disease. The aim of this work is to develop computer algorithms that can be used in the medical screening system for evaluating the condition of the retina leading to successful treatment. This work comprises five stages: 1) image pre-processing, 2) retinal structure extraction; 3) hard exudate detection, 4) red lesion detection and 5) grading of diabetic retinopathy. The aim of image pre-processing is to prepare the image with better quality where shade correction using morphological processes and contrast enhancement using fuzzy logic-based method are applied to the image. In the retinal structure extraction, multi-scale morphological technique and classification procedure are proposed for blood vessel detection. Vasculature loop-based method for the optic disc localisation is proposed, while for fovea localisation, a method based on its features and geometric relationships with the other retinal structures is developed. These methods have the advantage of lower computational complexity and competitive performance compared to the existing related methods. A novel coarse to fine strategy is proposed to detect hard exudates, where a local variation operator is used to calculate the standard deviation around each pixel followed by automated thresholding, morphological operations, and classification to segment coarse hard exudates. To fine-tune the result of coarse hard exudates, two region-based segmentation techniques are investigated to detect fine hard exudates. The significance of this method is manifested by its superior performance, lower computational complexity (compared to the current state of the art) and the ability to deal with a variety of image qualities. A novel red lesion detection method is proposed using mathematical morphology to segment candidate red lesions followed by refining them from traces of retinal structures and then a classification based on red lesion features is used to detect red lesions with high degree of discrimination between genuine red lesions and artifacts and as a result its detection performance has proved to be favourable. Grading of diabetic retinopathy is a very important stage after the detection of retinal lesions to evaluate their severity and to decide appropriate treatment. The most reliable medical approaches to diabetic retinopathy grading were investigated to build a novel computer-aided model for automated grading based on the clinical criteria and results of the earlier lesion segmentation. This model quantifies the nature, extent and spatial distribution of all the detected features and provides a clinical grading assessment. This is among the first of such models published and as such the novelty is considered to be one of the main contributions of this thesis.

Download or read book Automated Image Detection of Retinal Pathology written by Herbert Jelinek and published by CRC Press. This book was released on 2009-10-09 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discusses the Effect of Automated Assessment Programs on Health Care ProvisionDiabetes is approaching pandemic numbers, and as an associated complication, diabetic retinopathy is also on the rise. Much about the computer-based diagnosis of this intricate illness has been discovered and proven effective in research labs. But, unfortunately, many of

Download or read book DETECTION AND CLASSIFICATION OF DIABETIC RETINOPATHY CONDITION IN RETINAL IMAGES written by N. Ramakrishna and published by Archers & Elevators Publishing House. This book was released on with total page 96 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Automated Detection of Proliferative Diabetic Retinopathy from Retinal Images written by Roshan Alex Welikala and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Automated Retinal Image Analysis for Detection and Measurements of Tortuosity and Exudates written by and published by . This book was released on 2014 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last few decades, an automated retinal image analysis for a diabetic retinopathy has been a major area of attention in the computer vision. The typical approach used by Ophthalmologists for examining the eye is the pupil dilation. This takes time, is not accurate, and is uncomfortable for patients. On the other hand, the automated retinal image analysis for retina pathologies is more sophisticated technology by which Ophthalmologists could screen the retina of the eye regularly and find out its normal and abnormal structures in a more precise and comfortable way. Monitoring the retina of the eye, utilizing an automatic method, and by applying necessary cure in advance could save patients from losing their vision. In recent time, there were many research works on automated detection and classification of the features of the eye in the fundus [normal structures and abnormal structures (retina pathologies)] using different strategies and algorithms to obtain precise results. But they still do not meet many of the requirements. In this research we consider the retinal images taken from non-dilated eye pupils to eliminate the dilation process. These images are noisy, lower in contrast, lower in intensity, and have more non-uniform luminosity due to a non-dilation process and retinal camera. The contributions of this research are robust algorithms and methods that detect and extract as well as measure the landmark features of the retina such as the optic disc, and blood vessels as well as the abnormal structures such as blood vessel tortuosity, hard exudates and soft exudates (cotton wool spots), and an age-related macular degeneration (drusens). This provides early detection and monitoring of retina pathologies for a patient that can be cured by ophthalmologists prior to blindness. We investigated our developed algorithm by applying it to a number of retinal images with noise, low intensity, less color contrast, and non-uniform luminosity which are taken from non-dilated eye pupil. In addition to that, these images carry distinct kinds of retina pathologies such as exudates, drusens, and tortuosity.

Download or read book Automatic Detection and Analysis of Retinal Diseases written by Hillol Das and published by LAP Lambert Academic Publishing. This book was released on 2014-10-09 with total page 64 pages. Available in PDF, EPUB and Kindle. Book excerpt: Image processing and analysis has great significance in the field of medical science. One such area is the analysis of retinal fundus images. This book explains an automated system for detection and analysis of retinal diseases from fundus images. Common retinal diseases such as Diabetic Retinopathy, Retinitis Pigmentosa and Glaucoma are studied in detail and appropriate detection approaches has been discussed. These diseases usually causes vision loss that in many cases cannot be reversed in advanced stages whereas they can be controlled in the early stages otherwise it progresses to loss of central vision and leads to complete blindness. Experimental results shows very significant detection rate of the methods discussed especially in locating optic disk with normalized cross correlation function. The proposed automated detection system can therefore be deployed for mass screening of retinal fundus images for early detection of common retinal diseases in rural areas where there is non-availability of good number of ophthalmologist and reducing the screening cost in the same time.

Download or read book Artificial Intelligence in Ophthalmology written by Andrzej Grzybowski and published by Springer Nature. This book was released on 2021-10-13 with total page 280 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Diseases of the Macula written by Jack J. Kanski and published by . This book was released on 2002 with total page 236 pages. Available in PDF, EPUB and Kindle. Book excerpt: Liberally illustrated throughout with over 400 photographs (300 in full colour), this reference provides a practical and clinically oriented approach to the diagnosis and management of macular disorders. It covers not only diseases that primarily affect the macula, such as age-related macular degeneration, but also those that might have an indirect but never-the-less significant effect on macular function, such as vascular and inflammatory diseases. Many diseases in this book are illustrated with brief case studies, to help bring them to life and facilitate learning. With over 400 top quality clinical pictures, this book enables easy visual recognition of macular diseases. Covers all disorders associated with macular degeneration not only age-related macular degeneration. Includes case histories which is an invaluable and unique diagnostic tool that facilitates learning. Each chapter covers the most common disease first, followed by less common conditions which guides the reader towards an accurate diagnosis. Written as a quick and easy reference.

Download or read book Intelligent Pervasive Computing Systems for Smarter Healthcare written by Arun Kumar Sangaiah and published by John Wiley & Sons. This book was released on 2019-06-21 with total page 426 pages. Available in PDF, EPUB and Kindle. Book excerpt: A guide to intelligent decision and pervasive computing paradigms for healthcare analytics systems with a focus on the use of bio-sensors Intelligent Pervasive Computing Systems for Smarter Healthcare describes the innovations in healthcare made possible by computing through bio-sensors. The pervasive computing paradigm offers tremendous advantages in diversified areas of healthcare research and technology. The authors—noted experts in the field—provide the state-of-the-art intelligence paradigm that enables optimization of medical assessment for a healthy, authentic, safer, and more productive environment. Today’s computers are integrated through bio-sensors and generate a huge amount of information that can enhance our ability to process enormous bio-informatics data that can be transformed into meaningful medical knowledge and help with diagnosis, monitoring and tracking health issues, clinical decision making, early detection of infectious disease prevention, and rapid analysis of health hazards. The text examines a wealth of topics such as the design and development of pervasive healthcare technologies, data modeling and information management, wearable biosensors and their systems, and more. This important resource: Explores the recent trends and developments in computing through bio-sensors and its technological applications Contains a review of biosensors and sensor systems and networks for mobile health monitoring Offers an opportunity for readers to examine the concepts and future outlook of intelligence on healthcare systems incorporating biosensor applications Includes information on privacy and security issues on wireless body area network for remote healthcare monitoring Written for scientists and application developers and professionals in related fields, Intelligent Pervasive Computing Systems for Smarter Healthcare is a guide to the most recent developments in intelligent computer systems that are applicable to the healthcare industry.

Download or read book Computational Retinal Image Analysis written by Emanuele Trucco and published by Academic Press. This book was released on 2019-11-19 with total page 506 pages. Available in PDF, EPUB and Kindle. Book excerpt: Computational Retinal Image Analysis: Tools, Applications and Perspectives gives an overview of contemporary retinal image analysis (RIA) in the context of healthcare informatics and artificial intelligence. Specifically, it provides a history of the field, the clinical motivation for RIA, technical foundations (image acquisition modalities, instruments), computational techniques for essential operations, lesion detection (e.g. optic disc in glaucoma, microaneurysms in diabetes) and validation, as well as insights into current investigations drawing from artificial intelligence and big data. This comprehensive reference is ideal for researchers and graduate students in retinal image analysis, computational ophthalmology, artificial intelligence, biomedical engineering, health informatics, and more. Provides a unique, well-structured and integrated overview of retinal image analysis Gives insights into future areas, such as large-scale screening programs, precision medicine, and computer-assisted eye care Includes plans and aspirations of companies and professional bodies

Download or read book Digital Image Processing for Ophthalmology written by Xiaolu Zhu and published by Morgan & Claypool Publishers. This book was released on 2011-02-02 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundus images of the retina are color images of the eye taken by specially designed digital cameras. Ophthalmologists rely on fundus images to diagnose various diseases that affect the eye, such as diabetic retinopathy and retinopathy of prematurity. A crucial preliminary step in the analysis of retinal images is the identification and localization of important anatomical structures, such as the optic nerve head (ONH), the macula, and the major vascular arcades. Identification of the ONH is an important initial step in the detection and analysis of the anatomical structures and pathological features in the retina. Different types of retinal pathology may be detected and analyzed via the application of appropriately designed techniques of digital image processing and pattern recognition. Computer-aided analysis of retinal images has the potential to facilitate quantitative and objective analysis of retinal lesions and abnormalities. Accurate identification and localization of retinal features and lesions could contribute to improved diagnosis, treatment, and management of retinopathy. This book presents an introduction to diagnostic imaging of the retina and an overview of image processing techniques for ophthalmology. In particular, digital image processing algorithms and pattern analysis techniques for the detection of the ONH are described. In fundus images, the ONH usually appears as a bright region, white or yellow in color, and is indicated as the convergent area of the network of blood vessels. Use of the geometrical and intensity characteristics of the ONH, as well as the property that the ONH represents the location of entrance of the blood vessels and the optic nerve into the retina, is demonstrated in developing the methods. The image processing techniques described in the book include morphological filters for preprocessing fundus images, filters for edge detection, the Hough transform for the detection of lines and circles, Gabor filters to detect the blood vessels, and phase portrait analysis for the detection of convergent or node-like patterns. Illustrations of application of the methods to fundus images from two publicly available databases are presented, in terms of locating the center and the boundary of the ONH. Methods for quantitative evaluation of the results of detection of the ONH using measures of overlap and free-response receiver operating characteristics are also described. Table of Contents: Introduction / Computer-aided Analysis of Images of the Retina / Detection of Geometrical Patterns / Datasets and Experimental Setup / Detection of the\\Optic Nerve Head\\Using the Hough Transform / Detection of the\\Optic Nerve Head\\Using Phase Portraits / Concluding Remarks

Download or read book Diabetes and Fundus OCT written by Ayman S. El-Baz and published by Elsevier. This book was released on 2020-04-17 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Image Analysis and Modeling in Ophthalmology written by Eddie Y. K. Ng and published by CRC Press. This book was released on 2014-02-11 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital fundus images can effectively diagnose glaucoma and diabetes retinopathy, while infrared imaging can show changes in the vascular tissues. Likening the eye to the conventional camera, Image Analysis and Modeling in Ophthalmology explores the application of advanced image processing in ocular imaging. This book considers how images can be used to effectively diagnose ophthalmologic problems. It introduces multi-modality image processing algorithms as a means for analyzing subtle changes in the eye. It details eye imaging, textural imaging, and modeling, and highlights specific imaging and modeling techniques. The book covers the detection of diabetes retinopathy, glaucoma, anterior segment eye abnormalities, instruments on detection of glaucoma, and development of human eye models using computational fluid dynamics and heat transfer principles to predict inner temperatures of the eye from its surface temperature. It presents an ultrasound biomicroscopy (UBM) system for anterior chamber angle imaging and proposes an automated anterior segment eye disease classification system that can be used for early disease diagnosis and treatment management. It focuses on the segmentation of the blood vessels in high-resolution retinal images and describes the integration of the image processing methodologies in a web-based framework aimed at retinal analysis. The authors introduce the A-Levelset algorithm, explore the ARGALI system to calculate the cup-to-disc ratio (CDR), and describe the Singapore Eye Vessel Assessment (SIVA) system, a holistic tool which brings together various technologies from image processing and artificial intelligence to construct vascular models from retinal images. The text furnishes the working principles of mechanical and optical instruments for the diagnosis and healthcare administration of glaucoma, reviews state-of-the-art CDR calculation detail, and discusses the existing methods and databases. Image Analysis and Modeling in Ophthalmology includes the latest research development in the field of eye modeling and the multi-modality image processing techniques in ocular imaging. It addresses the differences, performance measures, advantages and disadvantages of various approaches, and provides extensive reviews on related fields.

Download or read book Automated Analysis of Retinal Images for Detection of Age related Macular Degeneration and Diabetic Retinopathy written by Mark Johannes Josephus Petrus van Grinsven and published by . This book was released on 2016 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Eye fundus image analysis for automatic detection of diabetic retinopathy written by Tomi Kauppi and published by . This book was released on 2010 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Fundamentals and Methods of Machine and Deep Learning written by Pradeep Singh and published by John Wiley & Sons. This book was released on 2022-02-01 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: FUNDAMENTALS AND METHODS OF MACHINE AND DEEP LEARNING The book provides a practical approach by explaining the concepts of machine learning and deep learning algorithms, evaluation of methodology advances, and algorithm demonstrations with applications. Over the past two decades, the field of machine learning and its subfield deep learning have played a main role in software applications development. Also, in recent research studies, they are regarded as one of the disruptive technologies that will transform our future life, business, and the global economy. The recent explosion of digital data in a wide variety of domains, including science, engineering, Internet of Things, biomedical, healthcare, and many business sectors, has declared the era of big data, which cannot be analysed by classical statistics but by the more modern, robust machine learning and deep learning techniques. Since machine learning learns from data rather than by programming hard-coded decision rules, an attempt is being made to use machine learning to make computers that are able to solve problems like human experts in the field. The goal of this book is to present a??practical approach by explaining the concepts of machine learning and deep learning algorithms with applications. Supervised machine learning algorithms, ensemble machine learning algorithms, feature selection, deep learning techniques, and their applications are discussed. Also included in the eighteen chapters is unique information which provides a clear understanding of concepts by using algorithms and case studies illustrated with applications of machine learning and deep learning in different domains, including disease prediction, software defect prediction, online television analysis, medical image processing, etc. Each of the chapters briefly described below provides both a chosen approach and its implementation. Audience Researchers and engineers in artificial intelligence, computer scientists as well as software developers.

Download or read book Diabetes and Fundus OCT written by Ayman S. El-Baz and published by Elsevier. This book was released on 2020-04-02 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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