• Chinese Optics Letters
  • Vol. 17, Issue 1, 011701 (2019)
C. Kharmyssov1, M. W. L. Ko2、*, and J. R. Kim1
Author Affiliations
  • 1School of Engineering, Nazarbayev University, Astana 010000, Kazakhstan
  • 2The University of Hong Kong, Pokfulam, Hong Kong, China
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    DOI: 10.3788/COL201917.011701 Cite this Article Set citation alerts
    C. Kharmyssov, M. W. L. Ko, J. R. Kim. Automated segmentation of optical coherence tomography images[J]. Chinese Optics Letters, 2019, 17(1): 011701 Copy Citation Text show less

    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.
    LRPE={(x,yRPE)|x[1,Nc],yRPE=min[I^(x,u)]},(1)

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    wab=2(ga+gb)+wmin,(2)

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    DiceTRT=2|TRTTRT0||TRT|+|TRT0|.(3)

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    AMRSDRPE=|RPE0RPE|×100%.(4)

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    RSPPRPE=TNRPETNRPE0×100%,(5)

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    RSPPILM=TNILMTNILM0×100%.(6)

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    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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