Skip to main content
SpringerLink
Log in
Book cover

International Conference on Intelligent Science and Big Data Engineering

IScIDE 2017: Intelligence Science and Big Data Engineering pp 597–607Cite as

Gradient Vector Flow Field and Fast Marching Based Method for Centerline Computation of Coronary Arteries

  • Conference paper
  • First Online:

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10559))

Abstract

This paper develops new concept of validating centerline extraction method of coronary arteries. The approach is based on the gradient vector flow (GVF) filed of the 3D segmented coronary arteries models. It is implemented with the Gaussian based speed image. The approach was validated over 3 three-dimensional synthetic vessel models and further tested in 3 clinical coronary arteries models reconstructed from computed tomography coronary angiography (CTCA) in human patients. The results showed an excellent agreement between the proposed method and ground truth centerline in synthetic vessel models. Second, the proposed method was applicable in both left coronary arteries and right coronary arteries with average processing time of 25.7 min per case. In conclusion, the proposed gradient vector flow field and fast marching based method should have more routine clinical applicability.

This is a preview of subscription content, log in via an institution.

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

References

  1. Cui, H., Wang, D., Wan, M., Zhang, J.M., Zhao, X., Tan, R.S., et al.: Fast marching and Runge-Kutta based method for centreline extraction of right coronary artery in human patients. Cardiovasc. Eng. Technol. 7(2), 159 (2016)

    Article  Google Scholar 

  2. Li, Z., Zhang, Y., Liu, G., Shao, H., Li, W., Tang, X.: A robust coronary artery identification and centerline extraction method in angiographies. Biomed. Sig. Proces. Control 16, 1–8 (2015)

    Article  Google Scholar 

  3. Yang, G., Kitslaar, P., Frenay, M., Broersen, A., Boogers, M.J., Bax, J.J., Dijkstra, J.: Automatic centerline extraction of coronary arteries in coronary computed tomographic angiography. Int. J. Cardiovasc. Imaging (Formerly Card. Imaging) 28(4), 921–933 (2012)

    Article  Google Scholar 

  4. Hassouna, M.S., Farag, A., et al.: Variational curve skeletons using gradient vector flow. IEEE Trans. Pattern Anal. Mach. Intell. 31(12), 2257–2274 (2009)

    Article  Google Scholar 

  5. Jain, A.K.: Fundamentals of Digital Image Processing. Prentice-Hall Inc., Upper Saddle River (1989)

    MATH  Google Scholar 

  6. Xu, C.Y., Prince, J.L.: Snakes, shapes, and gradient vector flow. IEEE Trans. Image Proces. 7(3), 359–369 (1998)

    Article  MathSciNet  MATH  Google Scholar 

  7. Courant, R., Hilbert, D.: Methods of Mathematical Physics, vol. 1. CUP Archive, Cambridge (1966)

    MATH  Google Scholar 

  8. Chang, S., Metaxas, D.N., Axel, L.: Scan-conversion algorithm for ridge point detection on tubular objects. In: Ellis, R.E., Peters, T.M. (eds.) MICCAI 2003. LNCS, vol. 2879, pp. 158–165. Springer, Heidelberg (2003). doi:10.1007/978-3-540-39903-2_20

    Chapter  Google Scholar 

  9. Zhang, S.Q., Zhou, J.Y., et al.: Centerline extraction for image segmentation using gradient and direction vector flow active contours. J. Sig. Inf. Process. 4(04), 407 (2013)

    Google Scholar 

  10. Süli, E., Mayers, D.F.: An Introduction to Numerical Analysis. Cambridge University Press, Cambridge (2003)

    Book  MATH  Google Scholar 

  11. Press, W.H., Teukolsky, S.A., Vetterling, W.T., Flannery, B.P.: Numerical Recipes in C, vol. 2. Cambridge University Press, Cambridge (1996)

    MATH  Google Scholar 

  12. Schaap, M., Metz, C.T., van Walsum, T., van der Giessen, A.G., Weustink, A.C., Mollet, N.R., Bauer, C., Bogunović, H., Castro, C., Deng, X., et al.: Standardized evaluation methodology and reference database for evaluating coronary artery centerline extraction algorithms. Med. Image Anal. 13, 701–714 (2009)

    Article  Google Scholar 

  13. Cui, H., Wang, D., Wan, M., Zhang, J.M., Zhao, X., Tan, S.Y., Wong, A.S.L., Tan, R.S., Huang, W., Xiong, W., Duan, Y., Zhou, J., Zhong, L.: Coronary artery segmentation via hessian filter and curve-skeleton extraction. In: 2014 IEEE Conference on Biomedical Engineering and Sciences (IECBES), pp. 93–98. IEEE (2014)

    Google Scholar 

Download references

Acknowledgments

The study was supported in part by the National Natural Science Foundation of China under Grants 61471297 and 61771397. We are very grateful to the National Heart Centre Singapore for the DICOM datasets.

Author information

Authors and Affiliations

  1. Shaanxi Key Lab of Speech and Image Information Processing (SAIIP), School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, 710072, PR China

    Hengfei Cui & Yong Xia

  2. Centre for Multidisciplinary Convergence Computing (CMCC), School of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an, 710072, PR China

    Hengfei Cui & Yong Xia

Authors
  1. Hengfei Cui
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yong Xia
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Yong Xia .

Editor information

Editors and Affiliations

  1. Dalian University of Technology, Dalian, China

    Yi Sun

  2. Dalian University of Technology, Dalian, China

    Huchuan Lu

  3. Dalian University of Technology, Dalian, China

    Lihe Zhang

  4. Nanjing University of Science and Technology, Nanjing, China

    Jian Yang

  5. Beijing Institute of Technology, Beijing, China

    Hua Huang

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Cui, H., Xia, Y. (2017). Gradient Vector Flow Field and Fast Marching Based Method for Centerline Computation of Coronary Arteries. In: Sun, Y., Lu, H., Zhang, L., Yang, J., Huang, H. (eds) Intelligence Science and Big Data Engineering. IScIDE 2017. Lecture Notes in Computer Science(), vol 10559. Springer, Cham. https://doi.org/10.1007/978-3-319-67777-4_54

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-67777-4_54

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-67776-7

  • Online ISBN: 978-3-319-67777-4

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation