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 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 Retinal Optical Coherence Tomography Image Analysis written by Xinjian Chen and published by Springer. This book was released on 2019-07-05 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces the latest optical coherence tomography (OCT) imaging and computerized automatic image analysis techniques, and their applications in the diagnosis and treatment of retinal diseases. Discussing the basic principles and the clinical applications of OCT imaging, OCT image preprocessing, as well as the automatic detection and quantitative analysis of retinal anatomy and pathology, it includes a wealth of clinical OCT images, and state-of-the-art research that applies novel image processing, pattern recognition and machine learning methods to real clinical data. It is a valuable resource for researchers in both medical image processing and ophthalmic imaging.
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 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 Handbook of Retinal Disease a Case based Approach written by Elias Reichel and published by JP Medical Ltd. This book was released on 2015-02-15 with total page 348 pages. Available in PDF, EPUB and Kindle. Book excerpt: Handbook of Retinal Disease offers the benefit of a case discussion by describing retinal disorders through real-life examples.The book features over 75 cases with high quality images and a highly structured, deductive approach.This book is the most clinically relevant guide possible to the latest imaging techniques used in the diagnosis of retinal diseases.
Download or read book High Resolution Imaging in Microscopy and Ophthalmology written by Josef F. Bille and published by Springer. This book was released on 2019-08-13 with total page 407 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book provides a comprehensive overview of the application of the newest laser and microscope/ophthalmoscope technology in the field of high resolution imaging in microscopy and ophthalmology. Starting by describing High-Resolution 3D Light Microscopy with STED and RESOLFT, the book goes on to cover retinal and anterior segment imaging and image-guided treatment and also discusses the development of adaptive optics in vision science and ophthalmology. Using an interdisciplinary approach, the reader will learn about the latest developments and most up to date technology in the field and how these translate to a medical setting. High Resolution Imaging in Microscopy and Ophthalmology – New Frontiers in Biomedical Optics has been written by leading experts in the field and offers insights on engineering, biology, and medicine, thus being a valuable addition for scientists, engineers, and clinicians with technical and medical interest who would like to understand the equipment, the applications and the medical/biological background. Lastly, this book is dedicated to the memory of Dr. Gerhard Zinser, co-founder of Heidelberg Engineering GmbH, a scientist, a husband, a brother, a colleague, and a friend.
Download or read book Automatic Analysis of Retinal Images written by Enrico Grisan and published by . This book was released on 2004 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Fundus Autofluorescence written by Noemi Lois and published by Lippincott Williams & Wilkins. This book was released on 2012-02-13 with total page 303 pages. Available in PDF, EPUB and Kindle. Book excerpt: Featuring over 250 illustrations, this detailed full-color textbook provides up-to-date information on the use of fundus autofluorescence imaging in evaluation of retinal disease. Chapters describe the techniques available to image and quantify fundus autofluorescence and the autofluorescence patterns observed in the healthy eye and in various retinal diseases. Emphasis is on the value of fundus autofluorescence as a diagnostic and prognostic tool and its clinical utility in the context of other imaging techniques, such as fluorescein and indocyanine green angiography and optical coherence tomography. Each chapter also discusses the value of fundus autofluorescence in understanding the pathogenesis of the condition, and provides a comprehensive update on all aspects of the condition. A companion Website will offer the fully searchable text and an image bank.
Download or read book Automatic Detection of Exudates in Retinal Fundus Images Using DMP written by Shraddha Trpathi and published by LAP Lambert Academic Publishing. This book was released on 2014-06-10 with total page 104 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains eight chapters encircles comprehensive study on exudates detection in retinal fundus images.automatic detection of exudates from retinal fundus images using DMP is very novel idea.In this book, we describe the methods of exudates detection and develop a new method.This method is very beneficial for diabetic retinopathy. with the help of this method we can easile identify the stage 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 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 Automatic Retinal Image Analysis to Triage Retinal Pathologies written by Renoh Johnson Chalakkal and published by . This book was released on 2019 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: Fundus retinal imaging is a non-invasive way of imaging the retina popular among the ophthalmic community and the targeted population. Over the past 15 years, extensive research and clinical studies using fundus images have been done for automatizing the screening and diagnosing process of three significant conditions affecting vision: macular edema, diabetic retinopathy, and glaucoma. These are the most important causes of preventable blindness around the globe, yet they can be successfully screened using the fundus image of the retina. Such diseases are associated with an observable variation in the structural and functional properties of the retina. Manual triage/diagnosis of these diseases is time-consuming and requires specialized ophthalmologists/optometrists; it is also expensive. Computer-aided medical triage/diagnosis can be applied to fundus retinal image analysis, thereby automatizing the triage. The process involves successfully combining sub-tasks focused at analyzing, locating, and segmenting different landmark structures inside a retina. The preliminary objective of this thesis is to develop automatic retinal image analysis (ARIA) techniques capable of analyzing, locating, and segmenting the key structures from the fundus image and combine them effectively to create a complete automatic screening system. First, the retinal vessel, which is the most important structure, is segmented. Two methods are developed for doing this: the first uses adaptive histogram equalization and anisotropic diffusion filtering, followed by weighted scaling and vessel edge enhancement. Fuzzy-C-mean classification, together with morphological transforms and connected component analysis, is applied to segment the vessel pixels. A second improved method for vessel segmentation is proposed, which is capable of segmenting the tiny peripheral vessel pixels missed by the first method. This method uses curvelet transform-based vessel edge enhancement technique followed by modified line operator-based vessel pixel segmentation. Second, a novel technique to automatically detect and segment important structures such as optic disc, macula, and fovea from a retinal image is developed. These structures, together with the retinal vessels, are considered as the retinal landmarks. The proposed method automatically detects the optic disc using histogram-based template matching combined with the maximum sum of vessel information. The optic disc region is segmented by using the Circular Hough Transform. For detecting fovea, the retinal image is uniformly divided into three horizontal stripes, and the strip including the detected optic disc, is selected. The contrast of the horizontal strip containing the optic disc region is then enhanced using a series of image processing steps. The macula region is first detected in the optic disc strip using various morphological operations and connected component analysis. The fovea is located inside this detected macular region. Next, an algorithm capable of analyzing the retinal image quality and content is developed. Often, methods focusing on ARIA use public retinal image databases for performance evaluation. The quality of images in such databases is often not evaluated as a pre-requisite for ARIA. Therefore, the performance metrics reported by such ARIA methods are inconsistent. Considering these facts, a deep learning-based approach to assess the quality of input retinal images is proposed. The method begins with a deep learning-based classification that identifies the image quality in terms of sharpness, illumination, and homogeneity, followed by an unsupervised second level that evaluates the field definition and content of the image. The proposed method is general and robust, making it more suitable than the alternative methods currently adopted in clinical practice. Finally, an automatic deep learning-based method for clinically significant macular edema triage is proposed. The classified high-quality retinal images are used as inputs. Both full image and ARIA processed image are experimented as the possible inputs. Deep convolutional neural networks are used as feature extractors. The extracted features are over-sampled to balance the highly skewed database samples across the examined classes. Finally, using the reduced feature set obtained through feature selection, a simple k-NN classifier demonstrates significant classification performance, thereby validating the preliminary objective of this study.
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 Retinal image analysis by mixture model based clustering and discriminant analysis for automatic detection of hard exudates and haemorrhages written by Clara Isabel Sánchez Gutiérrez and published by . This book was released on 2008 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Evidence Based Eye Care written by Peter J. Kertes and published by Lippincott Williams & Wilkins. This book was released on 2013-09-05 with total page 688 pages. Available in PDF, EPUB and Kindle. Book excerpt: Now in a revised and updated Second Edition, this handy guide to eye care uses evidence from the latest clinical trials to deliver practical advice directly applicable to the challenges of daily ophthalmic practice. Helpful illustrations and tables support the text and improve outcomes.
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.
