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Two-Steps Coronary Artery Segmentation Algorithm Based on Improved Level Set Model in Combination with Weighted Shape-Prior Constraints

  • Image & Signal Processing
  • Published:
Journal of Medical Systems Aims and scope Submit manuscript

Abstract

Due to the complex topological structure of the coronary artery and the uneven distribution of the contrast agent, the angiography images are inevitably blurred and has low contrast, which causes great difficulty in process of segmentation. For this problem, a two-steps segmentation algorithm based on Hessian matrix and level set is proposed in this paper. Firstly, potential blood vessels of coronary images are preliminary extracted via Hessian matrix eigenvalues feature vectors of the geometric features and the response function. Then a novel regularization and area constraint is introduced into the local data energy fitting functional. Finally, the precision of Coronary Artery image is obtained in the evolution of the level set function. Experiments show that our proposed algorithm has better performance to these comparison segmentation algorithms.

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Authors and Affiliations

  1. Department of Radiology, The Affiliated Huaian No.1 People’s Hospital of Nanjing Medical University, Huaian, 223300, Jiangsu, China

    Shang Ge, Zhaofei Shi, Guangming Peng & Zhaohuan Zhu

Authors
  1. Shang Ge
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  2. Zhaofei Shi
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  3. Guangming Peng
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  4. Zhaohuan Zhu
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Correspondence to Zhaohuan Zhu.

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Ge, S., Shi, Z., Peng, G. et al. Two-Steps Coronary Artery Segmentation Algorithm Based on Improved Level Set Model in Combination with Weighted Shape-Prior Constraints. J Med Syst 43, 210 (2019). https://doi.org/10.1007/s10916-019-1329-y

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