Mr. Zhuli Sun Profile

Zhuli Sun

at Soochow Univ

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Proceedings Article | 20 March 2015 Paper

Automated segmentation of serous pigment epithelium detachment in SD-OCT images

Zhuli Sun, Fei Shi, Dehui Xiang, Haoyu Chen, Xinjian Chen

Proceedings Volume 9413, 94133Q (2015) https://doi.org/10.1117/12.2078095

KEYWORDS: Image segmentation, Mathematical morphology, Image processing, Image processing algorithms and systems, Image analysis, Retina, 3D image processing, Speckle, Diagnostics, Anisotropic diffusion

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Pigment epithelium detachment (PED) is an important clinical manifestation of multiple chorio-retinal disease processes, which can cause the loss of central vision. A 3-D method is proposed to automatically segment serous PED in SD-OCT images. The proposed method consists of five steps: first, a curvature anisotropic diffusion filter is applied to remove speckle noise. Second, the graph search method is applied for abnormal retinal layer segmentation associated with retinal pigment epithelium (RPE) deformation. During this process, Bruch’s membrane, which doesn’t show in the SD-OCT images, is estimated with the convex hull algorithm. Third, the foreground and background seeds are automatically obtained from retinal layer segmentation result. Fourth, the serous PED is segmented based on the graph cut method. Finally, a post-processing step is applied to remove false positive regions based on mathematical morphology. The proposed method was tested on 20 SD-OCT volumes from 20 patients diagnosed with serous PED. The average true positive volume fraction (TPVF), false positive volume fraction (FPVF), dice similarity coefficient (DSC) and positive predictive value (PPV) are 97.19%, 0.03%, 96.34% and 95.59%, respectively. Linear regression analysis shows a strong correlation (r = 0.975) comparing the segmented PED volumes with the ground truth labeled by an ophthalmology expert. The proposed method can provide clinicians with accurate quantitative information, including shape, size and position of the PED regions, which can assist diagnose and treatment.

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