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A Statistical Model for 3D Segmentation of Retinal Choroid in Optical Coherence Tomography Images Publisher



Ghasemi F1 ; Rabbani H1
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Authors Affiliations
  1. 1. Biomedical Engineering Dept., Medical Image and Signal Processing Research Center, Isfahan University of Medical Sciences, Isfahan, Iran

Source: Progress in Biomedical Optics and Imaging - Proceedings of SPIE Published:2014


Abstract

The choroid is a densely layer under the retinal pigment epithelium (RPE). Its deeper boundary is formed by the sclera, the outer fibrous shell of the eye. However, the inhomogeneity within the layers of choroidal Optical Coherence Tomography (OCT)-tomograms presents a significant challenge to existing segmentation algorithms. In this paper, we performed a statistical study of retinal OCT data to extract the choroid. This model fits a Gaussian mixture model (GMM) to image intensities with Expectation Maximization (EM) algorithm. The goodness of fit for proposed GMM model is computed using Chi-square measure and is obtained lower than 0.04 for our dataset. After fitting GMM model on OCT data, Bayesian classification method is employed for segmentation of the upper and lower border of boundary of retinal choroid. Our simulations show the signed and unsigned error of -1.44 +/- 0.5 and 1.6 +/- 0.53 for upper border, and -5.7 +/- 13.76 and 6.3 +/- 13.4 for lower border, respectively. © 2014 SPIE.
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