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Abstract #82871 Published in IGR 20-4
Automated Iris Segmentation from Anterior Segment OCT Images with Occludable Angles via Local Phase Tensor
Shang Q; Shang Q; Zhao Y; Chen Z; Hao H; Hao H; Li F; Zhang X; Liu JConference proceedings : Annual International Conference of the IEEE Engineering in Medicine and Biology Society 2019; 2019: 4745-4749
Morphological changes in the iris are one of the major causes of angle-closure glaucoma, and an anteriorly-bowed iris may be further associated with greater risk of disease progression from primary angle-closure suspect (PACS) to chronic primary angle-closure glaucoma (CPCAG). In consequence, the automated detection of abnormalities in the iris region is of great importance in the management of glaucoma. In this paper, we present a new method for the extraction of the iris region by using a local phase tensor-based curvilinear structure enhancement method, and apply it to anterior segment optical coherence tomography (AS-OCT) imagery in the presence of occludable iridocorneal angle. The proposed method is evaluated across a dataset of 200 anterior chamber angle (ACA) images, and the experimental results show that the proposed method outperforms existing state-of-the-art method in applicability, effectiveness, and accuracy.
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Classification:
6.9.5 Other (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis)
6.9.2.1 Anterior (Part of: 6 Clinical examination methods > 6.9 Computerized image analysis > 6.9.2 Optical coherence tomography)
2.8 Iris (Part of: 2 Anatomical structures in glaucoma)
