Digital image processing for ophthalmology : detection of the optic nerve head /

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Bibliographic Details
Author / Creator:Zhu, Xiaolu.
Imprint:San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, c2011.
Description:1 electronic text (xii, 90 p.) : ill., digital file.
Language:English
Series:Synthesis lectures on biomedical engineering, 1930-0336 ; # 40
Synthesis digital library of engineering and computer science.
Synthesis lectures on biomedical engineering, # 40.
Subject:Optic nerve -- Imaging.
Eye -- Imaging.
Image processing -- Digital techniques.
Diagnostic Imaging.
Optic Nerve.
Eye.
Format: E-Resource Book
URL for this record:http://pi.lib.uchicago.edu/1001/cat/bib/10510980
Hidden Bibliographic Details
Other authors / contributors:Rangayyan, Rangaraj M.
Ells, Anna L.
ISBN:9781608456321 (electronic bk.)
9781608456314 (pbk.)
Notes:Part of: Synthesis digital library of engineering and computer science.
Series from website.
Includes bibliographical references (p. 77-83) and index.
Abstract freely available; full-text restricted to subscribers or individual document purchasers.
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Mode of access: World Wide Web.
System requirements: Adobe Acrobat Reader.
Summary: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.
Standard no.:10.2200/S00335ED1V01Y201102BME040