Computational Methods And Deep Learning For Ophthalmology
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Computational Methods And Deep Learning For Ophthalmology
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Author : D. Jude Hemanth
language : en
Publisher: Elsevier
Release Date : 2023-02-18
Computational Methods And Deep Learning For Ophthalmology written by D. Jude Hemanth and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-02-18 with Science categories.
Computational Methods and Deep Learning for Ophthalmology presents readers with the concepts and methods needed to design and use advanced computer-aided diagnosis systems for ophthalmologic abnormalities in the human eye. Chapters cover computational approaches for diagnosis and assessment of a variety of ophthalmologic abnormalities. Computational approaches include topics such as Deep Convolutional Neural Networks, Generative Adversarial Networks, Auto Encoders, Recurrent Neural Networks, and modified/hybrid Artificial Neural Networks. Ophthalmological abnormalities covered include Glaucoma, Diabetic Retinopathy, Macular Degeneration, Retinal Vein Occlusions, eye lesions, cataracts, and optical nerve disorders. This handbook provides biomedical engineers, computer scientists, and multidisciplinary researchers with a significant resource for addressing the increase in the prevalence of diseases such as Diabetic Retinopathy, Glaucoma, and Macular Degeneration. Presents the latest computational methods for designing and using Decision-Support Systems for ophthalmologic disorders in the human eye Conveys the role of a variety of computational methods and algorithms for efficient and effective diagnosis of ophthalmologic disorders, including Diabetic Retinopathy, Glaucoma, Macular Degeneration, Retinal Vein Occlusions, eye lesions, cataracts, and optical nerve disorders Explains how to develop and apply a variety of computational diagnosis systems and technologies, including medical image processing algorithms, bioinspired optimization, Deep Learning, computational intelligence systems, fuzzy-based segmentation methods, transfer learning approaches, and hybrid Artificial Neural Networks
Artificial Intelligence And Ophthalmology
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Author : Parul Ichhpujani
language : en
Publisher: Springer Nature
Release Date : 2021-04-22
Artificial Intelligence And Ophthalmology written by Parul Ichhpujani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-04-22 with Medical categories.
The book helps to explore the vast expanse of artificial intelligence-based scientific content that has been published in the last few years. Ophthalmology has recently undergone a silent digital revolution, with machine learning and deep learning algorithms consistently outperforming human graders in studies published across the globe. It is high time that a resource that breaks this information behemoth into easily digestible bits comes to the fore. This book simplifies the complex mechanics of algorithms used in ophthalmology and vision science applications. It also tries to address potential ethical issues with machines entering our clinics and patients’ lives. Overall it is essential reading for ophthalmologists/eye care professionals interested in artificial intelligence and everyone who is looking for a deep dive into the exciting world of digital medicine.
Computational Retinal Image Analysis
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Author : Emanuele Trucco
language : en
Publisher: Academic Press
Release Date : 2019-11-19
Computational Retinal Image Analysis written by Emanuele Trucco and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-19 with Computers categories.
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
Artificial Intelligence In Ophthalmology
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Author : Andrzej Grzybowski
language : en
Publisher: Springer Nature
Release Date : 2021-10-13
Artificial Intelligence In Ophthalmology written by Andrzej Grzybowski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-10-13 with Medical categories.
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.
Advanced Methods And Deep Learning In Computer Vision
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Author : E. R. Davies
language : en
Publisher: Academic Press
Release Date : 2021-11-09
Advanced Methods And Deep Learning In Computer Vision written by E. R. Davies and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-09 with Computers categories.
Advanced Methods and Deep Learning in Computer Vision presents advanced computer vision methods, emphasizing machine and deep learning techniques that have emerged during the past 5–10 years. The book provides clear explanations of principles and algorithms supported with applications. Topics covered include machine learning, deep learning networks, generative adversarial networks, deep reinforcement learning, self-supervised learning, extraction of robust features, object detection, semantic segmentation, linguistic descriptions of images, visual search, visual tracking, 3D shape retrieval, image inpainting, novelty and anomaly detection. This book provides easy learning for researchers and practitioners of advanced computer vision methods, but it is also suitable as a textbook for a second course on computer vision and deep learning for advanced undergraduates and graduate students. Provides an important reference on deep learning and advanced computer methods that was created by leaders in the field Illustrates principles with modern, real-world applications Suitable for self-learning or as a text for graduate courses
Intelligent Analysis Of Fundus Images Methods And Applications
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Author : Yuanyuan Chen
language : en
Publisher: World Scientific
Release Date : 2023-06-15
Intelligent Analysis Of Fundus Images Methods And Applications written by Yuanyuan Chen and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-15 with Computers categories.
This comprehensive compendium designs deep neural network models and systems for intelligent analysis of fundus imaging. In response to several blinding fundus diseases such as Retinopathy of Prematurity (ROP), Diabetic Retinopathy (DR) and Macular Edema (ME), different image acquisition devices and fundus image analysis tasks are elaborated.From the actual fundus disease analysis tasks, various deep neural network models and experimental results are constructed and analyzed. For each task, an actual system for clinical application is developed.This useful reference text provides theoretical and experimental reference basis for AI researchers, system engineers of intelligent medicine and ophthalmologists.
Handbook Of Research On Computer Vision And Image Processing In The Deep Learning Era
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Author : Srinivasan, A.
language : en
Publisher: IGI Global
Release Date : 2022-10-21
Handbook Of Research On Computer Vision And Image Processing In The Deep Learning Era written by Srinivasan, A. and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-21 with Computers categories.
In recent decades, there has been an increasing interest in using machine learning and, in the last few years, deep learning methods combined with other vision and image processing techniques to create systems that solve vision problems in different fields. There is a need for academicians, developers, and industry-related researchers to present, share, and explore traditional and new areas of computer vision, machine learning, deep learning, and their combinations to solve problems. The Handbook of Research on Computer Vision and Image Processing in the Deep Learning Era is designed to serve researchers and developers by sharing original, innovative, and state-of-the-art algorithms and architectures for applications in the areas of computer vision, image processing, biometrics, virtual and augmented reality, and more. It integrates the knowledge of the growing international community of researchers working on the application of machine learning and deep learning methods in vision and robotics. Covering topics such as brain tumor detection, heart disease prediction, and medical image detection, this premier reference source is an exceptional resource for medical professionals, faculty and students of higher education, business leaders and managers, librarians, government officials, researchers, and academicians.
Computational Pathology And Ophthalmic Medical Image Analysis
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Author : Danail Stoyanov
language : en
Publisher: Springer
Release Date : 2018-09-13
Computational Pathology And Ophthalmic Medical Image Analysis written by Danail Stoyanov and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-13 with Computers categories.
This book constitutes the refereed joint proceedings of the First International Workshop on Computational Pathology, COMPAY 2018, and the 5th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2018, held in conjunction with the 21st International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2018, in Granada, Spain, in September 2018. The 19 full papers (out of 25 submissions) presented at COMPAY 2018 and the 21 full papers (out of 31 submissions) presented at OMIA 2018 were carefully reviewed and selected. The COMPAY papers focus on artificial intelligence and deep learning. The OMIA papers cover various topics in the field of ophthalmic image analysis.
Computational Analysis Of The Human Eye With Applications
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Author : Sumeet Dua
language : en
Publisher: World Scientific
Release Date : 2011
Computational Analysis Of The Human Eye With Applications written by Sumeet Dua and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011 with Medical categories.
Advances in semi-automated high-throughput image data collection routines, coupled with a decline in storage costs and an increase in high-performance computing solutions have led to an exponential surge in data collected by biomedical scientists and medical practitioners. Interpreting this raw data is a challenging task, and nowhere is this more evident than in the field of opthalmology. The sheer speed at which data on cataracts, diabetic retinopathy, glaucoma and other eye disorders are collected, makes it impossible for the human observer to directly monitor subtle, yet critical details. This book is a novel and well-timed endeavor to present, in an amalgamated format, computational image modeling methods as applied to various extrinsic scientific problems in ophthalmology. It is self-contained and presents a highly comprehensive array of image modeling algorithms and methodologies relevant to ophthalmologic problems. The book is the first of its kind, bringing eye imaging and multi-dimensional hyperspectral imaging and data fusion of the human eye, into focus. The editors are at the top of their fields and bring a strong multidisciplinary synergy to this visionary volume. Their "inverted-pyramid" approach in presenting the content and their focus on core applications will appeal to students and practitioners in the field.
Deep Learning In Computer Vision
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Author : Mahmoud Hassaballah
language : en
Publisher: CRC Press
Release Date : 2020-03-23
Deep Learning In Computer Vision written by Mahmoud Hassaballah and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-03-23 with Computers categories.
Deep learning algorithms have brought a revolution to the computer vision community by introducing non-traditional and efficient solutions to several image-related problems that had long remained unsolved or partially addressed. This book presents a collection of eleven chapters where each individual chapter explains the deep learning principles of a specific topic, introduces reviews of up-to-date techniques, and presents research findings to the computer vision community. The book covers a broad scope of topics in deep learning concepts and applications such as accelerating the convolutional neural network inference on field-programmable gate arrays, fire detection in surveillance applications, face recognition, action and activity recognition, semantic segmentation for autonomous driving, aerial imagery registration, robot vision, tumor detection, and skin lesion segmentation as well as skin melanoma classification. The content of this book has been organized such that each chapter can be read independently from the others. The book is a valuable companion for researchers, for postgraduate and possibly senior undergraduate students who are taking an advanced course in related topics, and for those who are interested in deep learning with applications in computer vision, image processing, and pattern recognition.