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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
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