Chinese Optics Letters, 2019, 17 (1): 011701, Published Online: Jan. 17, 2019  

Automated segmentation of optical coherence tomography images Download: 544次

Author Affiliations
1 School of Engineering, Nazarbayev University, Astana 010000, Kazakhstan
2 The University of Hong Kong, Pokfulam, Hong Kong, China
Abstract
We propose a fast and accurate automated algorithm to segment retinal pigment epithelium and internal limiting membrane layers from spectral domain optical coherence tomography (SDOCT) B-scan images. A hybrid algorithm, which combines intensity thresholding and graph-based algorithms, was used to process and analyze SDOCT radial scans (120 B scans) images obtained from twenty patients. The relative difference in position of the layers segmented by the proposed hybrid algorithm and by the clinical expert was 1.49% ± 0.01%. The processing time of the hybrid algorithm was 9.3 s for six B scans. Dice’s coefficient of the hybrid algorithm was 96.7% ± 1.6%. The proposed hybrid algorithm for the segmentation of SDOCT images had good agreement with manual segmentation and reduced processing time.

C. Kharmyssov, M. W. L. Ko, J. R. Kim. Automated segmentation of optical coherence tomography images[J]. Chinese Optics Letters, 2019, 17(1): 011701.

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