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Automated segmentation of Optical Coherence Tomography images

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摘要

We propose a fast and accurate automated algorithm to segment retinal pigment epithelium and internal limiting membrane layer from spectral-domain optical coherence tomography (SDOCT) B-scans images. A hybrid algorithm, which combines intensity thresholding and graph-based algorithms, was used to process and analyze SDOCT radial scans (a hundred and twenty B-scans) images obtained from twenty patients. The relative difference in position of the layers segmented by the proposed hybrid algorithm and by clinical expert was 1.49% ± 0.01%. The processing time of the hybrid algorithm was 9.3 s for six B-scans. The 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.

Newport宣传-MKS新实验室计划
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作者单位:

    Nazarbayev University
    The University of Hong Kong
    Nazarbayev University

引用该论文

Kharmyssov Chingis,Ko Match,Kim Jong R.. Automated segmentation of Optical Coherence Tomography images[J].Chinese Optics Letters,2019,17(1):01.