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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.
This book presents cutting-edge research and applications of deep learning in a broad range of medical imaging scenarios, such as computer-aided diagnosis, image segmentation, tissue recognition and classification, and other areas of medical and healthcare problems. Each of its chapters covers a topic in depth, ranging from medical image synthesis and techniques for muskuloskeletal analysis to diagnostic tools for breast lesions on digital mammograms and glaucoma on retinal fundus images. It also provides an overview of deep learning in medical image analysis and highlights issues and challenges encountered by researchers and clinicians, surveying and discussing practical approaches in general and in the context of specific problems. Academics, clinical and industry researchers, as well as young researchers and graduate students in medical imaging, computer-aided-diagnosis, biomedical engineering and computer vision will find this book a great reference and very useful learning resource.
An essential resource for both general ophthalmologists and pediatric and retina specialists, Pediatric Retina, Third Edition, offers a comprehensive overview of all aspects of diagnosis and treatment of major medical and surgical diseases in this challenging field. Dr. Mary Elizabeth Hartnett, along with internationally acclaimed physicians, surgeons, and scientists, guides you through today’s best practices for retinal diseases in infants and children. Hundreds of superb, full-color images (many new to this edition), as well as clinical videos online, provide clear visual support. This is the tablet version which does not include access to the videos mentioned in the text.
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.
Arguably the most important ancillary test available to ophthalmologists worldwide, optical coherence tomography (OCT) has revolutionized the field, and now includes angiographic evaluations (OCTA) that provide vascular flow data without eye injection. Handbook of Retinal OCT is an easy-to-use, high-yield guide to both OCT and OCTA imaging for practitioners at any stage of their career. Highly templated, concise, and portable, this revised edition helps you master the latest imaging methods used to evaluate retinal disease, uveitis, and optic nerve disorders. - Helps all health professionals with an interest in OCT to better and more quickly interpret OCT imaging, offering quick, highly visual guidance for evaluating age-related macular degeneration, diabetic retinopathy, retinal vein occlusion, and much more. - Provides quick answers with bulleted, templated chapters, each focused on one specific diagnosis or group of diagnoses with a particular OCT appearance. - Demonstrates how the full spectrum of diseases presents through approximately 400 illustrations, including the highest-quality spectral-domain OCT images available and more than 50 new OCTA images. - Includes five new chapters covering optic nerve disease with retinal findings, pachychoroid diseases, paracentral acute middle maculopathy (PAMM), auto-immune retinopathies, and primary uveal lymphoma. - Offers clear visual guidance on image patterns with multiple arrows and labels throughout to highlight key details of each disease.
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.
The ability to see deeply affects how human beings perceive and interpret the world around them. For most people, eyesight is part of everyday communication, social activities, educational and professional pursuits, the care of others, and the maintenance of personal health, independence, and mobility. Functioning eyes and vision system can reduce an adult's risk of chronic health conditions, death, falls and injuries, social isolation, depression, and other psychological problems. In children, properly maintained eye and vision health contributes to a child's social development, academic achievement, and better health across the lifespan. The public generally recognizes its reliance on sight and fears its loss, but emphasis on eye and vision health, in general, has not been integrated into daily life to the same extent as other health promotion activities, such as teeth brushing; hand washing; physical and mental exercise; and various injury prevention behaviors. A larger population health approach is needed to engage a wide range of stakeholders in coordinated efforts that can sustain the scope of behavior change. The shaping of socioeconomic environments can eventually lead to new social norms that promote eye and vision health. Making Eye Health a Population Health Imperative: Vision for Tomorrow proposes a new population-centered framework to guide action and coordination among various, and sometimes competing, stakeholders in pursuit of improved eye and vision health and health equity in the United States. Building on the momentum of previous public health efforts, this report also introduces a model for action that highlights different levels of prevention activities across a range of stakeholders and provides specific examples of how population health strategies can be translated into cohesive areas for action at federal, state, and local levels.
This book provides the reader with a comprehensive set of instructions and examples of how to perform an economic evaluation of a health intervention, focusing solely on cost-effectiveness analysis in healthcare.
A state-of-the-art review of key topics in medical image perception science and practice, including associated techniques, illustrations and examples. This second edition contains extensive updates and substantial new content. Written by key figures in the field, it covers a wide range of topics including signal detection, image interpretation and advanced image analysis (e.g. deep learning) techniques for interpretive and computational perception. It provides an overview of the key techniques of medical image perception and observer performance research, and includes examples and applications across clinical disciplines including radiology, pathology and oncology. A final chapter discusses the future prospects of medical image perception and assesses upcoming challenges and possibilities, enabling readers to identify new areas for research. Written for both newcomers to the field and experienced researchers and clinicians, this book provides a comprehensive reference for those interested in medical image perception as means to advance knowledge and improve human health.