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A Semi-Automatic Coronary Artery Segmentation Framework Using Mechanical Simulation

  • Systems-Level Quality Improvement
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

CVD (cardiovascular disease) is one of the biggest threats to human beings nowadays. An early and quantitative diagnosis of CVD is important in extending lifespan and improving people’s life quality. Coronary artery stenosis can prevent CVD. To diagnose the degree of stenosis, the inner diameter of coronary artery needs to be measured. To achieve such measurement, the coronary artery is segmented by using a method that is based on morphology and the continuity between computed tomography image slices. A centerline extraction method based on mechanical simulation is proposed. This centerline extraction method can figure out a basic framework of the coronary artery by simulating pixel dots of the artery image into mass points. Such mass points have tensile forces, with which the outer pixel dots can be drawn to the center. Subsequently, the centerline of the coronary artery can be outlined by using the local line-fitting method. Finally, the nearest point method is adopted to measure the inner diameter. Experimental results showed that the methods proposed in this paper can precisely extract the centerline of the coronary artery and can accurately measure its inner diameter, thereby providing a basis for quantitative diagnosis of coronary artery stenosis.

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Acknowledgments

This research was funded by the Guangdong Natural Science Foundation under Grant No.S2013040014993, the State Scholarship Fund under Grant CSC NO.201408440326,the Pearl River S&T Nova Program of Guangzhou under Grant No.2014J2200049 and No.201506010035, the Guangdong Provincial Science and Technology Program under Grant No.2013B090600057 and No.2014A020215006, the Fundamental Research Funds for the Central Universities under Grant No.2014ZG003D.

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Authors and Affiliations

  1. School of Information Science and Technology, Zhongkai University of Agriculture and Engineering, Zhongkai Road 501#, Guangzhou, 510225, Guangdong, China

    Ken Cai

  2. Department of Biomedical Engineering, South China University of Technology, HEMC, Guangzhou, 510006, Guangdong, China

    Rongqian Yang & Lihua Li

  3. Department of Radiology, General Hospital of Guangzhou Military Command of PLA, Liuhua Road 111#, Guangzhou, 510010, Guangdong, China

    Ken Cai, Shanxing Ou, Yuke Chen & Jianhong Dou

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  1. Ken Cai
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  2. Rongqian Yang
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  3. Lihua Li
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  4. Shanxing Ou
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  5. Yuke Chen
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  6. Jianhong Dou
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Correspondence to Rongqian Yang.

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This article is part of the Topical Collection on Systems-Level Quality Improvement

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Cai, K., Yang, R., Li, L. et al. A Semi-Automatic Coronary Artery Segmentation Framework Using Mechanical Simulation. J Med Syst 39, 129 (2015). https://doi.org/10.1007/s10916-015-0329-9

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  • DOI: https://doi.org/10.1007/s10916-015-0329-9

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