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Automated segmentation of optical coherence tomography images

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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.

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DOI:10.3788/col201917.011701

所属栏目:Medical optics and biotechnology

基金项目:This work was supported by the NU ORAU research grant (No. SOE2017004), Nazarbayev University. The authors thank Prof. Christopher K. S. Leung from the Chinese University of Hong Kong for providing the OCT datasets for this study and for proofreading this manuscript.

收稿日期:2018-08-10

录用日期:2018-11-22

网络出版日期:2018-12-25

作者单位    点击查看

C. Kharmyssov:School of Engineering, Nazarbayev University, Astana 010000, Kazakhstan
M. W. L. Ko:The University of Hong Kong, Pokfulam, Hong Kong, China
J. R. Kim:School of Engineering, Nazarbayev University, Astana 010000, Kazakhstan

联系人作者:M. W. L. Ko(matchkoust@gmail.com)

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引用该论文

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

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