Abstract
High resolution images of the choroid can be obtained using Enhanced Depth Imaging Optical Coherence Tomography (EDI-OCT). The thickness of the choroid can be measured from these images and is used widely in clinical application for diagnosing various eye related diseases. But analysis of the choroidal thickness is presently done manually which varies with the observer and is a time consuming task. In this paper we propose a two stage contour evolution approach using chan vese method for the segmentation of choroidal layers in EDI OCT images. First the EDI OCT image is prefiltered using Rotating Kernel Transformation (RKT) to reduce the effect of speckle noise. This is followed by first stage of contour evolution which effectively identifies the upper boundary, the Bruchs Membrane (BM). The second level of segmentation delineates the lower boundary of the choroid, the Choroid Sclera Interface (CSI). The choroid thickness measured as the distance between BM and CSI are compared with the manually segmented results by an ophthalmologist. Results show good consistency with the proposed method.
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Neetha, G., Jiji, C.V. (2018). A Two Stage Contour Evolution Approach for the Measurement of Choroid Thickness in EDI-OCT Images. In: Rameshan, R., Arora, C., Dutta Roy, S. (eds) Computer Vision, Pattern Recognition, Image Processing, and Graphics. NCVPRIPG 2017. Communications in Computer and Information Science, vol 841. Springer, Singapore. https://doi.org/10.1007/978-981-13-0020-2_38
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DOI: https://doi.org/10.1007/978-981-13-0020-2_38
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