alexa Automatic anterior chamber angle assessment for HD-OCT images.
Bioinformatics & Systems Biology

Bioinformatics & Systems Biology

Journal of Computer Science & Systems Biology

Author(s): Tian J, Marziliano P, Baskaran M, Wong HT, Aung T

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Abstract Angle-closure glaucoma is a major blinding eye disease and could be detected by measuring the anterior chamber angle in the human eyes. High-definition OCT (Cirrus HD-OCT) is an emerging noninvasive, high-speed, and high-resolution imaging modality for the anterior segment of the eye. Here, we propose a novel algorithm which automatically detects a new landmark, Schwalbe's line, and measures the anterior chamber angle in the HD-OCT images. The distortion caused by refraction is corrected by dewarping the HD-OCT images, and three biometric measurements are defined to quantitatively assess the anterior chamber angle. The proposed algorithm was tested on 40 HD-OCT images of the eye and provided accurate measurements in about 1 second. This article was published in IEEE Trans Biomed Eng and referenced in Journal of Computer Science & Systems Biology

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