Plaque region segmentation of intracoronary optical cohenrence tomography images based on kernel graph cuts_Journal of Biomedical Engineering

Authors：

ZHANG Bo ¹ , YANG Jianli ¹ , WANG Guanglei ¹ , WANG Hongrui ¹ , LIU Xiuling ¹ ,  HAN Yechen ²

1. College of Eletronic and Information Engineering, Hebei University, Baoding, Hebei 071002, P.R.China;
2. Department of Cardiology, Chinese Academy of Medical Sciences & Peking Union Medical College Hospital, Beijing 100730, P.R.China;

Corresponding author：

HAN Yechen, Email: bobogg2005@hotmail.com

Keywords：

plaque region segmentation; intracoronary optical coherence tomography image; graph cuts

DOI：

10.7507/1001-5515.201606010

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The segmentation of the intracoronary optical coherence tomography (OCT) images is the basis of the plaque recognition, and it is important to the following plaque feature analysis, vulnerable plaque recognition and further coronary disease aided diagnosis. This paper proposes an algorithm about multi region plaque segmentation based on kernel graph cuts model that realizes accurate segmentation of fibrous, calcium and lipid pool plaques in coronary OCT image, while boundary information has been well reserved. We segmented 20 coronary images with typical plaques in our experiment, and compared the plaque regions segmented by this algorithm to the plaque regions obtained by doctor's manual segmentation. The results showed that our algorithm is accurate to segment the plaque regions. This work has demonstrated that it can be used for reducing doctors' working time on segmenting plaque significantly, reduce subjectivity and differences between different doctors, assist clinician's diagnosis and treatment of coronary artery disease.

Citation： ZHANGBo, YANGJianli, WANGGuanglei, WANGHongrui, LIUXiuling, HANYechen. Plaque region segmentation of intracoronary optical cohenrence tomography images based on kernel graph cuts. Journal of Biomedical Engineering, 2017, 34(1): 15-20. doi: 10.7507/1001-5515.201606010 Copy

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1. 林霖, 刘映峰, 缪绯. 冠状动脉易损斑块的检测方法进展. 实用医学杂志, 2014(9): 1353-1355.
2. 王守亮. 冠状动脉易损斑块评价方法研究进展. 山东医药, 2015(10): 100-102.
3. Athanasiou L S, Bourantas C V, Rigas G A, et al. Fully automated Calcium detection using optical coherence tomography//35th Annual International Coference of the IEEE EMBS. Osaka,Japan, 2013: 1430-1433.
4. WANG Z, Hiroyuki K, Hiram G B, et al. Automatic segmentation of intravascular optical coherence tomography images for facilitating quantitative diagnosis of athrosclerosis. SPIE-The International Society for Optical Engineering, 2011, 7889(1): 78890N-78890N-7.
5. Prakash A, Hewko M D, Sowa M, et al. Texture based segmentation method to detect atherosclerotic plaque from optical tomography images.// European Conference on Biomedical Optics VI. Munich, Germany, 2013.
6. Prakash A, Hewko M D, Sowa M, et al. Detection of atherosclerotic plaque from optical coherence tomography images using texture-based segmentation. Medical Technologies in Medicine/ Sovremennye,Tehnologii v Medicine, 2015, 7(1): 21-28.
7. 王千, 王成, 冯振元, 等. K-means 聚类算法研究综述. 电子设计工程, 2012, 20(7): 21-24.
8. Ben Salah M, Mitiche A, Ben Ayed I. Multiregion image segmentation by parametric kernel graph cuts. IEEE Trans Image Process, 2011, 20(2): 545-557.
9. Kubo T, XU Chenyang, WANG Zhao, et al. Plaque and thrombus evaluation by optical coherence tomography. Int J Cardiovasc Imaging, 2011, 27(2): 289-298.
10. Athanasiou L, Bourantas C, Rigas G, et al. Methodology for fully automated segmentation and plaque characterization in intracoronary optical coherence tomography images. J Biomed Opt, 2014, 19(2): 026009.

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