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

Author: Xiaolu Zhu; Rangaraj M Rangayyan; Anna L Ells
Publisher: San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA) : Morgan & Claypool, ©2011.
Series: Synthesis lectures on biomedical engineering, #40.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
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  Read more...
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Genre/Form: Electronic books
Additional Physical Format: Print version:
Zhu, Xiaolu.
Digital image processing for ophthalmology.
[San Rafael, Calif.] : Morgan & Claypool, ©2011
(OCoLC)783990783
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Xiaolu Zhu; Rangaraj M Rangayyan; Anna L Ells
ISBN: 9781608456321 1608456323
OCLC Number: 704257560
Notes: Part of: Synthesis digital library of engineering and computer science.
Series from website.
Description: 1 online resource (xii, 90 pages) : illustrations, digital file.
Contents: 1. Introduction --
Diagnostic imaging of the eye --
Anatomy and physiology of the eye --
Diseases and conditions that affect the retina --
Imaging of the retina --
Interpretation of images of the retina --
Computer-aided diagnosis of diseases affecting the eye --
Scope and organization of the book. 2. Computer-aided analysis of images of the retina --
Detection of anatomical features of the retina --
Detection of the optic nerve head --
Detection of the macula --
Detection of blood vessels --
Detection of abnormal features --
Longitudinal analysis of images --
Remarks. 3. Detection of geometrical patterns --
Filters for preprocessing images --
Detection of edges --
Prewitt and Sobel operators --
The Canny method --
Detection of oriented structures --
The matched filter --
The Gabor filter --
Detection of geometrical patterns --
The Hough transform --
Phase portraits --
Remarks. 4. Datasets and experimental setup --
The drive dataset --
The STARE dataset --
Scale factor for converting between the two datasets --
Annotation of images of the retina --
Evaluation of the results of detection --
Measures of distance and overlap --
Free-response receiver operating characteristics --
Remarks. 5. Detection of the optic nerve head using the Hough transform --
Derivation of the edge map --
Analysis of the Hough space --
Procedure for the detection of the ONH --
Selection of the circle using the reference intensity --
Results of detection of the optic nerve head --
Discussion --
Remarks. 6. Detection of the optic nerve head using phase portraits --
Derivation of the orientation field --
Analysis of the node map --
Results of detection of the optic nerve head --
Discussion --
Comparative analysis --
Remarks. 7. Concluding remarks --
References --
Authors' biographies --
Index.
Series Title: Synthesis lectures on biomedical engineering, #40.
Other Titles: Synthesis digital library of engineering and computer science.
Responsibility: Xiaolu Zhu, Rangaraj M. Rangayyan, Anna L. Ells.

Abstract:

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.

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Primary Entity

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