Computational Retinal Image Analysis
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Computational Retinal Image Analysis
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.
Computational Analysis Of The Human Eye With Applications
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 focus on core applications, will appeal to students and practitioners in the field.
Image Analysis and Modeling in Ophthalmology
Successful thermal modeling of the human eye helps in the early diagnosis of eye abnormalities such as inflammation, cataracts, diabetic retinopathy, and glaucoma-all leading causes of blindness. This book presents a unified work of eye imaging and modeling techniques that have been proposed and applied to ophthalmologic problems. It delves into various morphological, texture, higher order spectra, and wavelet transformation techniques used to extract important diagnostic features from images, which can then be analyzed by a data scientist for automated diagnosis.