Abstract
Segmentation of retinal layers with central serious chorioretinopathy (CSC) in Spectral Domain Optical Coherence Tomography (SD-OCT) images is significant for quantitative analysis including the volume, location and shape of CSC region. In this paper, we present an automatic segmentation method to segment retinal layers based on graph theory and the previous B-scan information. Firstly, the boundaries of Vitreous-ILM (inner limiting membrane), ONL (outer nuclear layer)-IS (photoreceptor inner segments) or LR (lesion region)-RPE (retinal pigment epithelium), and RPE-Choroid are estimated based on graph search model. Next, a flexible search region is constructed by calculating the thickness between Vitreous-ILM and ONL-IS based on the difference between two consecutive B-scans, which is used to refine the ONL-IS. The proposed method was quantitatively evaluated in total of 200 B-scan images from 5 abnormal cubes with CSC and 5 normal cubes, where we choose 20 B-scan images randomly in each cube. Experimental results illustrated that the proposed method can segment retinal layers in SD OCT images with CSC accurately. And the overall mean absolute boundary positioning differences and the overall mean absolute thickness differences compared to manual segmentation results are 3.68 ± 2.96 μm and 5.84 ± 4.78 μm.
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Acknowledgements
The authors sincerely thank the reviewers whose valuable comments have improved this paper. The work is supported by the National Natural Science Foundation of China under Grant No. 61701192, 61671242, 61671220, the Natural Science Foundation of Shandong Province, China, under Grant No. ZR2017QF004, China Postdoctoral Science Foundation under Grants No. 2017M612178, the Shandong Provincial Key R&D Program (2016ZDJS01A12), the National Key Research and Development Program of China (No. 2016YFC0106000), The Shandong Provincial Key Research and Development Project (2017CXGC0810), the Open Fund Project of Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education (Nanjing University of Science and Technology) (No.JYB201707). The authors would like to thank Prof. Songtao Yuan for helping to collect data. K. Gao and W. Kong performed most of the experiments, data analysis and manuscript writing. Prof. Dengwang Li and Prof. Yuehui Chen gave critically reviewed the study proposal and technical editing. Prof. Sijie Niu provided scientific proposals, conception, analysis and technical editing.
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Gao, K., Kong, W., Niu, S. et al. Automatic retinal layer segmentation in SD-OCT images with CSC guided by spatial characteristics. Multimed Tools Appl 79, 4417–4428 (2020). https://doi.org/10.1007/s11042-019-7395-9
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DOI: https://doi.org/10.1007/s11042-019-7395-9