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

The monitoring of the effects of retinopathy on the visual system can be assisted by analyzing the vascular architecture of the retina. This book presents methods based on Gabor filters to detect blood vessels in fundus images of the retina. Forty images of the retina from the Digital Retinal Images for Vessel Extraction (DRIVE) database were used to evaluate the performance of the methods. The results demonstrate high efficiency in the detection of blood vessels with an area under the receiver operating characteristic curve of 0.96. Monitoring the openness of the major temporal arcade (MTA) could facilitate improved diagnosis and optimized treatment of retinopathy. This book presents methods for the detection and modeling of the MTA, including the generalized Hough transform to detect parabolic forms. Results obtained with 40 images of the DRIVE database, compared with hand-drawn traces of the MTA, indicate a mean distance to the closest point of about 0.24mm. This book illustrates applications of the methods mentioned above for the analysis of the effects of proliferative diabetic retinopathy and retinopathy of prematurity on retinal vascular architecture.

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.

Overview of the status of the broad range of laser applications.

Noninvasive Diagnostic Techniques in Ophthalmology explores the special noninvasive tools developed to function as diagnostic indicators and to further our understanding of ocular function. The volume's focus is on new development in instrumentation and techniques for studying the cornea, lens, retina, vitreous, and aqueous dynamics; whereby special attention is given to how each technique has improved our understanding of basic processes and diagnostic capability. Theoretical aspects, possible sources of error, current problems and limitations, safety evaluation, and future applications and directions are considered. Topics examined include ophthalmic image processing; magnetic resonance imaging of the eye and orbit; diagnostic ocular ultrasound; corneal topography; holographic contour analysis of the cornea; wide field and color specular microscopy; use of the Fourier transform method for statistical evaluation of corneal endothelial morphology; confocal microscopy; in vivo corneal redox fluorometry; evaluation of cataract function with the Scheimp-flug camera; fluorescence and Raman spectroscopy of the crystallin lens; in vivo uses of quasi-elastic light scattering; fundus reflectometry; and clinical visual psychophysics measurements. The book offers discussions of fractal analysis of human retinal blood vessel patterns, scanning laser tomography of the living human eye, fundus imaging and diagnostic screening for public health, and digital image processing for ophthalmology, as well as a detailed appendix comprising additional topics and sources.

Clear, concise, and clinical, this unique reference offers a comprehensive overview of the basic techniques needed for ocular examination and diagnosis. Abundantly illustrated, it presents the principles of each technique, provides guidance on choosing the appropriate approach, explains how to perform them, offers examples of when each technique should be used, and lists their common indications and potential pitfalls. Offers a full chapter covering new imaging techniques for the retina and optic nerve. Features abundantly illustrated guidance in a clear format for a quick visual reference. Explores standard assessment procedures as well as microbiological examination and investigation, ultrasound and radiological evaluation, clinical visual electrophysiology, and fluorescein angiography.

This book constitutes the refereed joint proceedings of the International Workshop on Fetal and Infant Image Analysis, FIFI 2017, and the 6th International Workshop on Ophthalmic Medical Image Analysis, OMIA 2017, held in conjunction with the 20th International Conference on Medical Imaging and Computer-Assisted Intervention, MICCAI 2017, in Québec City, QC, Canada, in September 2017. The 8 full papers presented at FIFI 2017 and the 20 full papers presented at OMIA 2017 were carefully reviewed and selected. The FIFI papers feature research on advanced image analysis approaches focused on the analysis of growth and development in the fetal, infant and paediatric period. The OMIA papers cover various topics in the field of ophthalmic image analysis.