Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images

Optical coherence tomography is a high resolution, rapid, and noninvasive diagnostic tool for angle closure glaucoma. In this paper, we present a new strategy for the classification of the angle closure glaucoma using morphological shape analysis of the iridocorneal angle. The angle structure config...

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Main Authors: Soe Ni Ni, J. Tian, Pina Marziliano, Hong-Tym Wong
Format: Article
Language:English
Published: Hindawi Limited 2014-01-01
Series:Journal of Ophthalmology
Online Access:http://dx.doi.org/10.1155/2014/942367
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spelling doaj-ef7a039706354842a6a38cb4b266cf3e2020-11-24T21:21:48ZengHindawi LimitedJournal of Ophthalmology2090-004X2090-00582014-01-01201410.1155/2014/942367942367Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT ImagesSoe Ni Ni0J. Tian1Pina Marziliano2Hong-Tym Wong3School of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, SingaporeSchool of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, SingaporeSchool of Electrical and Electronic Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, SingaporeDepartment of Ophthalmology, Tan Tock Seng Hospital, 11 Jalan Tan Tock Seng, 308433, SingaporeOptical coherence tomography is a high resolution, rapid, and noninvasive diagnostic tool for angle closure glaucoma. In this paper, we present a new strategy for the classification of the angle closure glaucoma using morphological shape analysis of the iridocorneal angle. The angle structure configuration is quantified by the following six features: (1) mean of the continuous measurement of the angle opening distance; (2) area of the trapezoidal profile of the iridocorneal angle centered at Schwalbe's line; (3) mean of the iris curvature from the extracted iris image; (4) complex shape descriptor, fractal dimension, to quantify the complexity, or changes of iridocorneal angle; (5) ellipticity moment shape descriptor; and (6) triangularity moment shape descriptor. Then, the fuzzy k nearest neighbor (fkNN) classifier is utilized for classification of angle closure glaucoma. Two hundred and sixty-four swept source optical coherence tomography (SS-OCT) images from 148 patients were analyzed in this study. From the experimental results, the fkNN reveals the best classification accuracy (99.11±0.76%) and AUC (0.98±0.012) with the combination of fractal dimension and biometric parameters. It showed that the proposed approach has promising potential to become a computer aided diagnostic tool for angle closure glaucoma (ACG) disease.http://dx.doi.org/10.1155/2014/942367
collection DOAJ
language English
format Article
sources DOAJ
author Soe Ni Ni
J. Tian
Pina Marziliano
Hong-Tym Wong
spellingShingle Soe Ni Ni
J. Tian
Pina Marziliano
Hong-Tym Wong
Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images
Journal of Ophthalmology
author_facet Soe Ni Ni
J. Tian
Pina Marziliano
Hong-Tym Wong
author_sort Soe Ni Ni
title Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images
title_short Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images
title_full Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images
title_fullStr Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images
title_full_unstemmed Anterior Chamber Angle Shape Analysis and Classification of Glaucoma in SS-OCT Images
title_sort anterior chamber angle shape analysis and classification of glaucoma in ss-oct images
publisher Hindawi Limited
series Journal of Ophthalmology
issn 2090-004X
2090-0058
publishDate 2014-01-01
description Optical coherence tomography is a high resolution, rapid, and noninvasive diagnostic tool for angle closure glaucoma. In this paper, we present a new strategy for the classification of the angle closure glaucoma using morphological shape analysis of the iridocorneal angle. The angle structure configuration is quantified by the following six features: (1) mean of the continuous measurement of the angle opening distance; (2) area of the trapezoidal profile of the iridocorneal angle centered at Schwalbe's line; (3) mean of the iris curvature from the extracted iris image; (4) complex shape descriptor, fractal dimension, to quantify the complexity, or changes of iridocorneal angle; (5) ellipticity moment shape descriptor; and (6) triangularity moment shape descriptor. Then, the fuzzy k nearest neighbor (fkNN) classifier is utilized for classification of angle closure glaucoma. Two hundred and sixty-four swept source optical coherence tomography (SS-OCT) images from 148 patients were analyzed in this study. From the experimental results, the fkNN reveals the best classification accuracy (99.11±0.76%) and AUC (0.98±0.012) with the combination of fractal dimension and biometric parameters. It showed that the proposed approach has promising potential to become a computer aided diagnostic tool for angle closure glaucoma (ACG) disease.
url http://dx.doi.org/10.1155/2014/942367
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