1. A Fast Algorithm for Automatic Detection of Anterior Chamber Angle Points and Measurement of Central Corneal Thickness for Anterior Chamber OCT Images

    A Fast Algorithm for Automatic Detection of Anterior Chamber Angle Points and Measurement of Central Corneal Thickness for Anterior Chamber OCT Images

    This paper proposed a fast algorithm to detect anterior chamber angle points and measure central corneal thickness for anterior chamber optical coherence tomography (OCT) images automatically. This algorithm uses biggest connected regions method to get the anterior chamber region, and detects the anterior chamber angle points (ACAPs) in this region firstly. Secondly, the algorithm uses ACAPs to obtain the real position of central cornea then measures the central corneal thickness of anterior chamber. The proposed algorithm was tested on 74 anterior chamber OCT images and provided accurate measurements in about 90 milliseconds.

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