Skip to main content
SpringerLink
Log in

Strengths and Pitfalls of Whole-Heart Atlas-Based Segmentation in Congenital Heart Disease Patients

  • Conference paper
  • First Online:
Reconstruction, Segmentation, and Analysis of Medical Images (RAMBO 2016, HVSMR 2016)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10129))

Abstract

Atlas-based whole-heart segmentation is a well-established technique for the extraction of key cardiac structures of the adult heart. Despite its relative success in this domain, its implementation in whole-heart segmentation of paediatric patients suffering from a form of congenital heart disease is not straightforward. The aim of this work is to evaluate the current strengths and limitations of whole-heart atlas based segmentation techniques within the context of the Whole-Heart and Great Vessel Segmentation from 3D Cardiovascular MRI in Congenital Heart Disease Challenge (HVSMR). Obtained results suggest that there are no significant differences in the accuracies of state-of-the-art methods, reporting maximum Dice scores of 0.73 for the myocardium and 0.90 for the blood pool.

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

Access this chapter

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

Institutional subscriptions

Notes

  1. 1.

    http://segchd.csail.mit.edu/index.html.

  2. 2.

    https://challenge.kitware.com/#submission/57dc2c02cad3a51cc66c8b12.

References

  1. Cardoso, M.J., Leung, K., Modat, M., Keihaninejad, S., Cash, D., Barnes, J., Fox, N.C., Ourselin, S.: Steps: similarity and truth estimation for propagated segmentations and its application to hippocampal segmentation and brain parcelation. Med. Image Anal. 17(6), 671–684 (2013)

    Article  Google Scholar 

  2. Gilbert, K., Cowan, B.R., Suinesiaputra, A., Occleshaw, C., Young, A.A.: Rapid D-Affine biventricular cardiac function with polar prediction. In: Golland, P., Hata, N., Barillot, C., Hornegger, J., Howe, R. (eds.) MICCAI 2014. LNCS, vol. 8674, pp. 546–553. Springer, Heidelberg (2014). doi:10.1007/978-3-319-10470-6_68

    Google Scholar 

  3. Iglesias, J.E., Sabuncu, M.R.: Multi-atlas segmentation of biomedical images: a survey. Med. Image Anal. 24(1), 205–219 (2015)

    Article  Google Scholar 

  4. Išgum, I., Staring, M., Rutten, A., Prokop, M., Viergever, M., van Ginneken, B.: Multi-atlas-based segmentation with local decision fusion application to cardiac and aortic segmentation in CT scans. IEEE Trans. Med. Imaging 28(7), 100–1010 (2009)

    Google Scholar 

  5. Jacobs, S., Grunert, R., Mohr, F.W., Falk, V.: 3D-imaging of cardiac structures using 3D heart models for planning in heart surgery: a preliminary study. Interact. Cardiovasc. Thorac. Surg. 7(1), 6–9 (2008)

    Article  Google Scholar 

  6. Kirisli, H.A., Schaap, M., Klein, S., Papadopoulou, S., Bonardi, M., Chen, C., Weustink, A., Mollet, N., Vonken, E.P.A., Geest, R., Walsum, T., Niessen, W.: Evaluation of a multi-atlas based method for segmentation of cardiac CTA data: a large-scale, multicenter, and multivendor study. Med. Phys. 37(12), 6279–6292 (2010)

    Article  Google Scholar 

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

    Article  Google Scholar 

  8. Marelli, A.J., Mackie, A.S., Ionescu-Ittu, R., Rahme, E., Pilote, L.: Congenital heart disease in the general population changing prevalence and age distribution. Circulation 115, 163–172 (2007)

    Article  Google Scholar 

  9. Ntsinjana, H.N., Hughes, M.L., Taylor, A.M.: The role of cardiovascular magnetic resonance in pediatric congenital heart disease. J. Cardiovasc. Magn. Reson. 13(51) (2011)

    Google Scholar 

  10. Pace, D.F., Dalca, A.V., Geva, T., Powell, A.J., Moghari, M.H., Golland, P.: Interactive whole-heart segmentation in congenital heart disease. In: Navab, N., Hornegger, J., Wells, W.M., Frangi, A.F. (eds.) MICCAI 2015. LNCS, vol. 9351, pp. 80–88. Springer, Heidelberg (2015). doi:10.1007/978-3-319-24574-4_10

    Chapter  Google Scholar 

  11. Prakash, A., Powell, A.J., Geva, T.: Multimodality noninvasive imaging for assessment of congenital heart disease. Circulation 3, 112–125 (2010)

    Google Scholar 

  12. Warfield, S., Zou, K., Wells, W.: Simultaneous truth and performance level estimation (staple): an algorithm for the validation of image segmentation. IEEE Trans. Med. Imaging 23(7), 903–921 (2004)

    Article  Google Scholar 

  13. Wren, C., O’Sullivan, J.: Survival with congenital heart disease and need for follow up in adult life. Heart 85, 438–443 (2001)

    Article  Google Scholar 

  14. Zhuang, X.: Challenges and methodologies of fully automatic whole heart segmentation: a review. J. Healthc. Eng. 4, 371–407 (2013)

    Article  Google Scholar 

  15. Zhuang, X., Rhode, K., Razavi, R., Hawkes, D., Ourselin, S.: A registration-based propagation framework for automatic whole heart segmentation of cardiac MRI. IEEE Trans. Med. Imaging 29(9), 1612–1625 (2010)

    Article  Google Scholar 

  16. Zuluaga, M.A., Burgos, N., Mendelson, A., Taylor, A., Ourselin, S.: Voxelwise atlas rating for computer assisted diagnosis: application to congenital heart diseases of the great arteries. Med. Image Anal. 26(1), 185–194 (2015)

    Article  Google Scholar 

  17. Zuluaga, M.A., Cardoso, M.J., Modat, M., Ourselin, S.: Multi-atlas propagation whole heart segmentation from MRI and CTA using a local normalised correlation coefficient criterion. In: Ourselin, S., Rueckert, D., Smith, N. (eds.) FIMH 2013. LNCS, vol. 7945, pp. 174–181. Springer, Heidelberg (2013). doi:10.1007/978-3-642-38899-6_21

    Chapter  Google Scholar 

Download references

Acknowledgements

This work was supported through an Innovative Engineering for Health award by the Wellcome Trust [WT101957]; Engineering and Physical Sciences Research Council (EPSRC) [NS/A000027/1]. BB is funded by UCL EPSRC Centre for Doctoral Training in Medical Imaging Scholarship Award. AMT and SS receive funding from Heart Research UK, the British Heart Foundation and the National Institute for Health Research Biomedical Research Centre at GOSH and UCL. SO receives funding from the National Institute for Health Research University College London Hospitals Biomedical Research Centre (NIHR BRC UCLH/UCL High Impact Initiative BW.mn.BRC10269) and the EPSRC (EP/K005278/1).

Author information

Authors and Affiliations

  1. Translational Imaging Group, Centre for Medical Image Computing, University College London, London, UK

    Maria A. Zuluaga, Tom Vercauteren & Sébastien Ourselin

  2. Department of Medical Physics and Biomedical Engineering, University College London, London, UK

    Benedetta Biffi

  3. Centre for Cardiovascular Imaging, UCL Institute of Cardiovascular Science & Great Ormond Street Hospital for Children, London, UK

    Benedetta Biffi, Andrew M. Taylor & Silvia Schievano

Authors
  1. Maria A. Zuluaga
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Benedetta Biffi
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Andrew M. Taylor
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Silvia Schievano
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Tom Vercauteren
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Sébastien Ourselin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Maria A. Zuluaga .

Editor information

Editors and Affiliations

  1. University College London, London, United Kingdom

    Maria A. Zuluaga

  2. King’s College London, London, United Kingdom

    Kanwal Bhatia

  3. Imperial College London, London, United Kingdom

    Bernhard Kainz

  4. Harvard Medical School and Boston Children’s Hospital, Boston, Massachusetts, USA

    Mehdi H. Moghari

  5. MIT, Cambridge, Massachusetts, USA

    Danielle F. Pace

Rights and permissions

Reprints and permissions

Copyright information

© 2017 Springer International Publishing AG

About this paper

Cite this paper

Zuluaga, M.A., Biffi, B., Taylor, A.M., Schievano, S., Vercauteren, T., Ourselin, S. (2017). Strengths and Pitfalls of Whole-Heart Atlas-Based Segmentation in Congenital Heart Disease Patients. In: Zuluaga, M., Bhatia, K., Kainz, B., Moghari, M., Pace, D. (eds) Reconstruction, Segmentation, and Analysis of Medical Images. RAMBO HVSMR 2016 2016. Lecture Notes in Computer Science(), vol 10129. Springer, Cham. https://doi.org/10.1007/978-3-319-52280-7_14

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-52280-7_14

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-52279-1

  • Online ISBN: 978-3-319-52280-7

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation