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Journal of Medical Imaging

Glaucoma progression detection using nonlocal Markov random field prior
Author(s): Akram Belghith; Christopher Bowd; Felipe A. Medeiros; Madhusudhanan Balasubramanian; Robert N. Weinreb; Linda M. Zangwill
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Paper Abstract

Glaucoma is neurodegenerative disease characterized by distinctive changes in the optic nerve head and visual field. Without treatment, glaucoma can lead to permanent blindness. Therefore, monitoring glaucoma progression is important to detect uncontrolled disease and the possible need for therapy advancement. In this context, three-dimensional (3-D) spectral domain optical coherence tomography (SD-OCT) has been commonly used in the diagnosis and management of glaucoma patients. We present a new framework for detection of glaucoma progression using 3-D SD-OCT images. In contrast to previous works that use the retinal nerve fiber layer thickness measurement provided by commercially available instruments, we consider the whole 3-D volume for change detection. To account for the spatial voxel dependency, we propose the use of the Markov random field (MRF) model as a prior for the change detection map. In order to improve the robustness of the proposed approach, a nonlocal strategy was adopted to define the MRF energy function. To accommodate the presence of false-positive detection, we used a fuzzy logic approach to classify a 3-D SD-OCT image into a “non-progressing” or “progressing” glaucoma class. We compared the diagnostic performance of the proposed framework to the existing methods of progression detection.

Paper Details

Date Published: 29 December 2014
PDF: 9 pages
J. Med. Imag. 1(3) 034504 doi: 10.1117/1.JMI.1.3.034504
Published in: Journal of Medical Imaging Volume 1, Issue 3
Show Author Affiliations
Akram Belghith, Univ. of California, San Diego (United States)
Christopher Bowd, Univ. of California, San Diego (United States)
Felipe A. Medeiros, Univ. of California, San Diego (United States)
Madhusudhanan Balasubramanian, The Univ. of Memphis (United States)
The Univ. of Tennessee Health Science Ctr. (United States)
Robert N. Weinreb, Univ. of California, San Diego (United States)
Linda M. Zangwill, Univ. of California, San Diego (United States)

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