Automated detection of glaucoma using elongated quinary patterns technique with optical coherence tomography angiogram images
Article
Chan, Yam Meng, Ng, E.Y.K., Jahmunah, V., Koh, Joel En Wei, Oh, Shu Lih, Han, Wei Shan, Yip, Leonard Wei Leon and Acharya, U. Rajendra. 2021. "Automated detection of glaucoma using elongated quinary patterns technique with optical coherence tomography angiogram images." Biomedical Signal Processing and Control. 69. https://doi.org/10.1016/j.bspc.2021.102895
Article Title | Automated detection of glaucoma using elongated quinary patterns technique with optical coherence tomography angiogram images |
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ERA Journal ID | 3391 |
Article Category | Article |
Authors | Chan, Yam Meng, Ng, E.Y.K., Jahmunah, V., Koh, Joel En Wei, Oh, Shu Lih, Han, Wei Shan, Yip, Leonard Wei Leon and Acharya, U. Rajendra |
Journal Title | Biomedical Signal Processing and Control |
Journal Citation | 69 |
Article Number | 102895 |
Number of Pages | 9 |
Year | 2021 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 1746-8094 |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.bspc.2021.102895 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S1746809421004924 |
Abstract | Glaucoma is the second most common cause of blindness worldwide after cataracts. It presents a great health concern as it is usually undetectable during the early stages without regular screening. Noticeable symptoms of glaucoma may only appear at a later stage. The eye disease progresses over time without treatment. Clinicians are specially trained to identify and diagnose glaucoma. However, reasons such as fatigue and observer errors may impair the clinician’s judgement. Hence, a trained computer-aided diagnosis system is necessary to prevent such issues. Optical coherence tomography angiography (OCTA) images were used to detect glaucoma. In this work, we have used elongated quinary patterns (EQP) technique to obtain multi-gradient magnitudes and angles. Various texture features are extracted from the various levels of gradients and angles of EQP images. Optimal features selected using Student’s t-test are fed to an ensemble classifier and 10-fold cross validation strategy is employed in which adaptive synthetic (ADASYN) is applied to reduce the bias. In this work, we have obtained an accuracy of 95.1% for the detection of left eye (OS) disc centered OCTA images. This developed system is available for further evaluation using more images. |
Keywords | Ten-fold validation ; Glaucoma; Optical coherence tomography angiography ; Elongated quinary patterns ; Ensemble classifier ; Image features |
ANZSRC Field of Research 2020 | 400306. Computational physiology |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Nanyang Technological University, Singapore |
Ngee Ann Polytechnic, Singapore | |
National Healthcare Group, Singapore | |
Asia University, Taiwan | |
Singapore University of Social Sciences (SUSS), Singapore | |
Kumamoto University, Japan |
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