Skip to main content

Segmentation of Left Ventricle in Cardiac Cine MRI: An Automatic Image-Driven Method

  • Conference paper
Functional Imaging and Modeling of the Heart (FIMH 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5528))

Abstract

This study investigates a fully automatic left ventricle segmentation method from cine short axis MR images. Advantages of this method include that it: 1) does not require manually drawn initial contours, trained statistical shape or gray-level appearance model; 2) provides not only endocardial and epicardial contours, but also papillary muscles and trabeculations’ contours; 3) introduces a roundness measure that is fast and automatically locates the left ventricle; 4) simplifies the epicardial contour segmentation by mapping the pixels from Cartesian to approximately polar coordinates; and 5) applies a fast Fourier transform to smooth the endocardial and epicardial contours. Quantitative evaluation was performed on 41 subjects. The average perpendicular distance between manually drawn and automatically selected contours over all slices, all studies, and two phases (end-diastole and end-systole) was 1.40±1.18 mm for endocardial and 1.75±1.15 mm for epicardial contours. These results indicate a promising method for automatic segmentation of left ventricle for clinical use.

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

Access this chapter

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 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

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Lorenzo-Valdés, M., Sanchez-Ortiz, G.I., Elkington, A.G., Mohiaddin, R.H., Rueckert, D.: Segmentation of 4D cardiac MR images using a probabilistic atlas and the EM algorithm. Med. Image Anal. 8(3), 255–265 (2004)

    Article  Google Scholar 

  2. Pednekar, A., Kurkure, U., Muthupillai, R., Flamm, S., Kakadiaris, I.A.: Automated left ventricular segmentation in cardiac MRI. IEEE Trans. Biomed. Eng. 53(7), 1425–1428 (2006)

    Article  Google Scholar 

  3. Uzümcü, M., van der Geest, R.J., Swingen, C., Reiber, J.H., Lelieveldt, B.P.: Time continuous tracking and segmentation of cardiovascular magnetic resonance images using multidimensional dynamic programming. Invest. Radiol. 41(1), 52–62 (2006)

    Article  Google Scholar 

  4. Rezaee, M.R., van der Zwet, P.J., Lelieveldt, B.E., van der Geest, R.J., Reiber, J.C.: A multi-resolution image segmentation technique based on pyramidal segmentation and fuzzy clustering. IEEE Trans. Image Process 9(7), 1238–1248 (2000)

    Article  Google Scholar 

  5. Kaus, M.R., von Berg, J., Weese, J., Niessen, W., Pekar, V.: Automated segmentation of the left ventricle in cardiac MRI. Med. Image Anal. 8(3), 245–254 (2004)

    Article  Google Scholar 

  6. Mitchell, S.C., Lelieveldt, B.P., van der Geest, R.J., Bosch, H.G., Reiber, J.H., Sonka, M.: Multistage hybrid active appearance model matching: segmentation of left and right ventricles in cardiac MR images. IEEE Trans. Med. Imaging 20(5), 415–423 (2001)

    Article  Google Scholar 

  7. Paragios, N.: A level set approach for shape-driven segmentation and tracking of the left ventricle. IEEE Trans. Med. Imaging 22(6), 773–776 (2003)

    Article  Google Scholar 

  8. Lynch, M., Ghita, O., Whelan, P.F.: Segmentation of the left ventricle of the heart in 3-D+t MRI data using an optimized nonrigid temporal model. IEEE Trans. Med. Imaging 27(2), 195–203 (2008)

    Article  Google Scholar 

  9. Fradkin, M., Ciofolo, C., Mory, B., Hautvast, G., Breeuwer, M.: Comprehensive segmentation of cine cardiac MR images. Med. Image. Comp. Comp. Assist. Interv. 11(pt 1), 178–185 (2008)

    Google Scholar 

  10. Ben Ayed, I., Lu, Y., Li, S., Ross, I.: Left ventricle tracking using overlap priors. Med. Image. Comp. Comp. Assist. Interv. 11(pt 1), 1025–1033 (2008)

    Google Scholar 

  11. Boykov, Y., Jolly, M.P.: Interactive Organ Segmentation Using Graph Cuts. In: Delp, S.L., DiGoia, A.M., Jaramaz, B. (eds.) MICCAI 2000. LNCS, vol. 1935, pp. 276–286. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  12. Lin, X., Cowan, B., Young, A.: Model-based Graph Cut Method for Segmentation of the Left Ventricle. In: Conf. Proc. IEEE Eng. Med. Biol. Soc., vol. 3, pp. 3059–3062 (2005)

    Google Scholar 

  13. Cocosco, C.A., Niessen, W.J., Netsch, T., Vonken, E.J., Lund, G., Stork, A., Viergever, M.A.: Automatic image-driven segmentation of the ventricles in cardiac cine MRI. J. Magn. Reson. Imaging 28(2), 366–374 (2008)

    Article  Google Scholar 

  14. Frangi, A.F., Niessen, W.J., Viergever, M.A.: Three-dimensional modeling for functional analysis of cardiac images: a review. IEEE Trans. Med. Imaging 20(1), 2–25 (2001)

    Article  Google Scholar 

  15. Otsu, N.: A Threshold Selection Method from Gray-Level Histograms. IEEE Transactions on Systems, Man, and Cybernetics 9(1), 62–66 (1979)

    Article  Google Scholar 

  16. Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn., ch. 4. Prentice-Hall, New Jersey (2001)

    Google Scholar 

  17. http://www.medis.nl/index.htm

  18. van Assen, H.C., Danilouchkine, M.G., Frangi, A.F., Ordás, S., Westenberg, J.J., Reiber, J.H., Lelieveldt, B.P.: SPASM: a 3D-ASM for segmentation of sparse and arbitrarily oriented cardiac MRI data. Med. Image Anal. 10(2), 286–303 (2006)

    Article  Google Scholar 

  19. Sorgel, W., Vaerman, V.: Automatic heart localization from 4D MRI datasets. SPIE: Med. Imag. 3034, 333–344 (1997)

    Google Scholar 

  20. Papavassiliu, T., Kühl, H.P., Schröder, M., Süselbeck, T., Bondarenko, O., Böhm, C.K., Beek, A., Hofman, M.M., van Rossum, A.C.: Effect of endocardial trabeculae on left ventricular measurements and measurement reproducibility at cardiovascular MR imaging. Radiology 236(1), 57–64 (2005)

    Article  Google Scholar 

  21. Weinsaft, J.W., Cham, M.D., Janik, M., Min, J.K., Henschke, C.I., Yankelevitz, D.F., Devereux, R.B.: Left ventricular papillary muscles and trabeculae are significant determinants of cardiac MRI volumetric measurements: effects on clinical standards in patients with advanced systolic dysfunction. Int. J. Cardiol. 126(3), 359–365 (2008)

    Article  Google Scholar 

  22. Lin, X., Cowan, B.R., Young, A.A.: Automated detection of left ventricle in 4D MR images: experience from a large study. Med. Image Comp. Comp. Assist. Interv. 9(pt 1), 728–735 (2006)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2009 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Lu, Y., Radau, P., Connelly, K., Dick, A., Wright, G.A. (2009). Segmentation of Left Ventricle in Cardiac Cine MRI: An Automatic Image-Driven Method. In: Ayache, N., Delingette, H., Sermesant, M. (eds) Functional Imaging and Modeling of the Heart. FIMH 2009. Lecture Notes in Computer Science, vol 5528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-01932-6_37

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-01932-6_37

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-01931-9

  • Online ISBN: 978-3-642-01932-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics