Skip to main content
SpringerLink
Log in

Multi-atlas Based Segmentation of Corpus Callosum on MRIs of Multiple Sclerosis Patients

  • Conference paper
  • First Online:
Pattern Recognition (GCPR 2014)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 8753))

Included in the following conference series:

Abstract

In this work, a supervised automatic multi-atlas based segmentation method for corpus callosum (CC) in magnetic resonance images (MRIs) of MS patients is presented. Due to atrophy, the shape of disease affected CC differs distinctively from healthy ones. Therefore, atlases are used that are built from the underlying dataset and do not originate from atlas datasets of healthy brains. The atlas construction is done by clustering the patient images into subgroups of similar images and building a mean image from each cluster. During this work, the optimal number of atlases and the best label fusion method are analyzed. The method is evaluated on 100 T1-weighted brain MRI images from MS patients. Accuracy is assessed by comparing the overlap of the segmentations from the developed method against manual segmentations obtained by a medical student.

Recommended for submission to YRF2014 by Prof. Dr.-Ing. Klaus Tönnies, Otto-von-Guericke University of Magdeburg.

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://fsl.fmrib.ox.ac.uk/fsl/fslwiki

  2. 2.

    Provided by ANTS toolbox (https://www.nitrc.org/projects/ants).

References

  1. Rohlfing, T., Brandt, R., Menzel, R., Maurer Jr., C.R.: Evaluation of atlas selection strategies for atlas-based image segmentation with application to confocal microscopy images of bee brains. NeuroImage 21(4), 1428–1442 (2004)

    Article  Google Scholar 

  2. Blezek, D.J., Miller, J.V.: Atlas stratification. Med. Image Anal. 11(5), 443–457 (2007)

    Article  Google Scholar 

  3. Edwards, S., Liu, C., Blumhardt, L.: Cognitive correlates of supratentorial atrophy on MRI in multiple sclerosis. Acta Neurol. Scand. 104(4), 214–223 (2001)

    Article  Google Scholar 

  4. Martola, J., Stawiarz, L., Frederikson, S., Hillert, J., Bergström, J., Flodmark, O., Kristoffersen Wilberg, M.: Progression of non-age-related callosal brain atrophy in multiple sclerosis: a 9-year longitudinal MRI study representing four decades of disease development. J. Neurol. Neurosurg. Psychiatry 78(4), 375–380 (2007)

    Google Scholar 

  5. Llufriu, S., Blanco, Y., Martinez-Heras, E., Casanova-Molla, J., Gabilondo, I., Sepulveda, M., Falcon, C., Berenguer, J., Bargallo, N., Villoslada, P.: Influence of corpus callosum damage on cognition and physical disability in multiple sclerosis: a multimodal study. PloS one 7(5), e37167 (2012)

    Article  Google Scholar 

  6. Avants, B.B., Epstein, C.L., Grossman, M., Gee, J.C.: Symmetric diffeomorphic image registration with cross-correlation: evaluating automated labeling of elderly and neurodegenerative brain. Med. Image Anal. 12(1), 26–41 (2008)

    Article  Google Scholar 

  7. Klein, A., Andersson, J., Ardekani, B.A., Ashburner, J., Avants, B., Chiang, M.-C., Christensen, G.E., Collins, D.L., Gee, J., Hellier, P.: Evaluation of 14 nonlinear deformation algorithms applied to human brain MRI registration. Neuroimage 46(3), 786–802 (2009)

    Article  Google Scholar 

  8. Jia, H., Wu, G., Wang, Q., Shen, D.: ABSORB: atlas building by self-organized registration and bundling. NeuroImage 51(3), 1057–1070 (2010)

    Article  Google Scholar 

  9. Avants, B.B., Yushkevich, P., Pluta, J., Minkoff, D., Korczykowski, M., Detre, J., Gee, J.C.: The optimal template effect in hippocampus studies of diseased populations. Neuroimage 49(3), 2457–2466 (2010)

    Article  Google Scholar 

  10. Yushkevich, P.A., Avants, B.B., Pluta, J., Das, S., Minkoff, D., Mechanic-Hamilton, D., Glynn, S., Pickup, S., Liu, W., Gee, J.C.: A high-resolution computational atlas of the human hippocampus from postmortem magnetic resonance imaging at 9.4 T. Neuroimage 442, 385–398 (2009)

    Article  Google Scholar 

  11. Warfield, S.K., Zou, K.H., Wells, W.M.: 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 

  12. Dice, L.R.: Measures of the amount of ecologic association between species. Ecology 26(3), 297–302 (1945)

    Article  Google Scholar 

  13. McAusland, J., Tam, R.C., Wong, E., Riddehough, A., Li, D.K.: Optimizing the use of radiologist seed points for improved multiple sclerosis lesion segmentation. IEEE Trans. Biomed. Eng. 57(11), 2689–2698 (2010)

    Article  Google Scholar 

Download references

Acknowledgements

This work arose during my internship at the MSMRI Research Group (University of British Columbia in Vancouver, Canada). The dataset that was used for development and evaluation was kindly provided by MSMRI.

Author information

Authors and Affiliations

  1. Otto-von-Guericke University of Magdeburg, Magdeburg, Germany

    Anneke Meyer

Authors
  1. Anneke Meyer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Anneke Meyer .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, University of Münster, Münster, Germany

    Xiaoyi Jiang

  2. Computer Science Department 5, University of Erlangen-Nürnberg, Erlangen, Germany

    Joachim Hornegger

  3. Department of Computer Science, University of Kiel, Kiel, Germany

    Reinhard Koch

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Meyer, A. (2014). Multi-atlas Based Segmentation of Corpus Callosum on MRIs of Multiple Sclerosis Patients. In: Jiang, X., Hornegger, J., Koch, R. (eds) Pattern Recognition. GCPR 2014. Lecture Notes in Computer Science(), vol 8753. Springer, Cham. https://doi.org/10.1007/978-3-319-11752-2_61

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-11752-2_61

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-11751-5

  • Online ISBN: 978-3-319-11752-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation