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13 March 2014 A statistical model for 3D segmentation of retinal choroid in optical coherence tomography images
F. Ghasemi, H. Rabbani
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Proceedings Volume 9038, Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging; 90381K (2014) https://doi.org/10.1117/12.2044101
Event: SPIE Medical Imaging, 2014, San Diego, California, United States
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.
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F. Ghasemi and H. Rabbani "A statistical model for 3D segmentation of retinal choroid in optical coherence tomography images", Proc. SPIE 9038, Medical Imaging 2014: Biomedical Applications in Molecular, Structural, and Functional Imaging, 90381K (13 March 2014); https://doi.org/10.1117/12.2044101
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KEYWORDS
Optical coherence tomography
Image segmentation
Expectation maximization algorithms
Data modeling
Statistical analysis
3D image processing
Error analysis
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