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 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 Intelligence Based Medicine written by Anthony C. Chang and published by Academic Press. This book was released on 2020-06-27 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligence-Based Medicine: Data Science, Artificial Intelligence, and Human Cognition in Clinical Medicine and Healthcare provides a multidisciplinary and comprehensive survey of artificial intelligence concepts and methodologies with real life applications in healthcare and medicine. Authored by a senior physician-data scientist, the book presents an intellectual and academic interface between the medical and the data science domains that is symmetric and balanced. The content consists of basic concepts of artificial intelligence and its real-life applications in a myriad of medical areas as well as medical and surgical subspecialties. It brings section summaries to emphasize key concepts delineated in each section; mini-topics authored by world-renowned experts in the respective key areas for their personal perspective; and a compendium of practical resources, such as glossary, references, best articles, and top companies. The goal of the book is to inspire clinicians to embrace the artificial intelligence methodologies as well as to educate data scientists about the medical ecosystem, in order to create a transformational paradigm for healthcare and medicine by using this emerging new technology. Covers a wide range of relevant topics from cloud computing, intelligent agents, to deep reinforcement learning and internet of everything Presents the concepts of artificial intelligence and its applications in an easy-to-understand format accessible to clinicians and data scientists Discusses how artificial intelligence can be utilized in a myriad of subspecialties and imagined of the future Delineates the necessary elements for successful implementation of artificial intelligence in medicine and healthcare
Download or read book Computer Aided Diagnosis of Diabetic Retinopathy written by Muhammad Nadeem Ashraf and published by LAP Lambert Academic Publishing. This book was released on 2015-09-03 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: Diabetic Retinopathy (DR) is vision threatening problem in diabetic patients and patient may suffers from complete blindness if untreated. Hemorrhages and Microaneurysms (HMAs) are the early signs that appear in retina at initial stages of DR. Early diagnosis of both Hemorrhages and Microaneurysms (HMAs) is crucial to prevent blindness. Continuous increase of diabetic cases in all over the world including Pakistan is limiting the typical manual screening capabilities. There is an urgent need of a robust automatic computer aided diagnosis (CAD) system using digital fundus images for the screening and monitoring of various types of DR to save many sight years of diabetic patients. Automatic detection of DR, especially detection of its early signs (HMAs), is still an open issue. Research work, described in this Book, is focusing on the analysis of various texture features of Region of Interests (ROIs) for the detection of HMAs using state-of-the-art texture descriptors Local Binary Pattern (LBP), which are independent of uneven illumination present in fundus images. This book would be helpful for the students & researchers working in the fields of medical and digital image processing.
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 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 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 Medical Data Analysis written by Alfredo Colosimo and published by . This book was released on 2002 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt:
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 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
Download or read book Image Analysis for Automatic Diagnosis of Diabetic Retinopathy written by Chanjira Sinthanayothin and published by . This book was released on 1999 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Quality Assessment of Retinal Fundus Images Using Elliptical Local Vessel Density written by and published by . This book was released on 2010 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Diabetic retinopathy is the leading cause of blindness in the Western world. The World Health Organisation estimates that 135 million people have diabetes mellitus worldwide and that the number of people with diabetes will increase to 300 million by the year 2025 (Amos et al., 1997). Timely detection and treatment for DR prevents severe visual loss in more than 50% of the patients (ETDRS, 1991). Through computer simulations is possible to demonstrate that prevention and treatment are relatively inexpensive if compared to the health care and rehabilitation costs incurred by visual loss or blindness (Javitt et al., 1994). The shortage of ophthalmologists and the continuous increase of the diabetic population limits the screening capability for effective timing of sight-saving treatment of typical manual methods. Therefore, an automatic or semi-automatic system able to detect various type of retinopathy is a vital necessity to save many sight-years in the population. According to Luzio et al. (2004) the preferred way to detect diseases such as diabetic retinopathy is digital fundus camera imaging. This allows the image to be enhanced, stored and retrieved more easily than film. In addition, images may be transferred electronically to other sites where a retinal specialist or an automated system can detect or diagnose disease while the patient remains at a remote location. Various systems for automatic or semi-automatic detection of retinopathy with fundus images have been developed. The results obtained are promising but the initial image quality is a limiting factor (Patton et al., 2006); this is especially true if the machine operator is not a trained photographer. Algorithms to correct the illumination or increase the vessel contrast exist (Chen & Tian, 2008; Foracchia et al., 2005; Grisan et al., 2006;Wang et al., 2001), however they cannot restore an image beyond a certain level of quality degradation. On the other hand, an accurate quality assessment algorithm can allow operators to avoid poor images by simply re-taking the fundus image, eliminating the need for correction algorithms. In addition, a quality metric would permit the automatic submission of only the best images if many are available. The measurement of a precise image quality index is not a straightforward task, mainly because quality is a subjective concept which varies even between experts, especially for images that are in the middle of the quality scale. In addition, image quality is dependent upon the type of diagnosis being made. For example, an image with dark regions might be considered of good quality for detecting glaucoma but of bad quality for detecting diabetic retinopathy. For this reason, we decided to define quality as the 'characteristics of an image that allow the retinopathy diagnosis by a human or software expert'. Fig. 1 shows some examples of macula centred fundus images whose quality is very likely to be judged as poor by many ophthalmologists. The reasons for this vary. They can be related to the camera settings like exposure or focal plane error (Fig. 1.(a, e, f)), the camera condition like a dirty or shuttered lens (Fig. 1.(d, h)), the movements of the patient which might blur the image (Fig. 1.(c)) or if the patient is not in the field of view of the camera (Fig. 1.(g)). We define an outlier as any image that is not a retina image which could be submitted to the screening system by mistake. Existing algorithms to estimate the image quality are based on the length of visible vessels in the macula region (Fleming et al., 2006), or edges and luminosity with respect to a reference image (Lalonde et al., 2001; Lee & Wang, 1999). Another method uses an unsupervised classifier that employs multi-scale filterbanks responses (Niemeijer et al., 2006). The shortcomings of these methods are either the fact that they do not take into account the natural variance encountered in retinal images or that they require a considerable time to produce a result. Additionally, none of the algorithms in the literature that we surveyed generate a 'quality measure'. Authors tend to split the quality levels into distinct classes and to classify images in particular ones. This approach is not really flexible and is error prone. In fact human experts are likely to disagree if many categories of image quality are used. Therefore, we think that a normalized 'quality measure' from 0 to 1 is the ideal way to approach the classification problem. Processing speed is another aspect to be taken into consideration. While algorithms to assess the disease state of the retina do not need to be particularly fast (within reason), the time response of the quality evaluation method is key towards the development of an automatic retinopathy screening system.
Download or read book 7th International Conference on Advancements of Medicine and Health Care through Technology written by Simona Vlad and published by Springer Nature. This book was released on 2022-01-01 with total page 452 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gathers the proceedings of the 7th International Conference on Advancements of Medicine and Health Care through Technology, held virtually on 13 – 15 October 2020, from Cluj-Napoca, Romania. It reports on both theoretical and practical developments fostering the use of cutting-edge technology in clinical settings, telemedicine, and biological research. Chapters mainly deal with medical devices, measurements and instrumentation, medical imaging and biological signal processing and health care information systems. Further topics include modeling, simulation and biomechanics, as well as innovative (bio-)materials for biomedical applications. The conference, as well as the realization of this book, was supported by the Romanian Society for Medical Engineering and Biological Technology.
Download or read book Signal and Image Processing Techniques for the Development of Intelligent Healthcare Systems written by E. Priya and published by Springer Nature. This book was released on 2020-09-21 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively reviews the various automated and semi-automated signal and image processing techniques, as well as deep-learning-based image analysis techniques, used in healthcare diagnostics. It highlights a range of data pre-processing methods used in signal processing for effective data mining in remote healthcare, and discusses pre-processing using filter techniques, noise removal, and contrast-enhanced methods for improving image quality. The book discusses the status quo of artificial intelligence in medical applications, as well as its future. Further, it offers a glimpse of feature extraction methods for reducing dimensionality and extracting discriminatory information hidden in biomedical signals. Given its scope, the book is intended for academics, researchers and practitioners interested in the latest real-world technological innovations.
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 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 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
