Skip to main content
SpringerLink
Log in

Stroke Lesion Segmentation of 3D Brain MRI Using Multiple Random Forests and 3D Registration

  • Conference paper
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries (BrainLes 2015)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9556))

Included in the following conference series:

Abstract

Stroke is a common cause of sudden death and disability worldwide. In clinical practice, brain magnetic resonance (MR) scans are used to assess the stroke lesion presence. In this work, we have built a fully automatic stroke lesion segmentation system using 3D brain magnetic resonance (MR) data. The system contains a 3D registration framework and a 3D multi-random forest model trained from the data provided by the Ischemic Stroke Lesion Segmentation (ISLES) challenge of the 18th International Conference on Medical Image Computing and Computer Assisted Intervention. The preliminary test results show that the presented system is capable to detect stroke lesion from 3D brain MRI data.

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

References

  1. Burger, W., Burge, M.J.: Digital Image Processing - An Algorithmic Introduction Using Java. Springer, Heidelberg (2008)

    Google Scholar 

  2. Binmore, K., Davies, J.: Calculus Concepts and Methods. Cambridge University Press, Cambridge (2007)

    MATH  Google Scholar 

  3. Feichtinger, H.G., Strohmer, T.: Gabor Analysis Algorithms: Theory and Applications. Birkhuser, Basel (1999)

    MATH  Google Scholar 

  4. Koenderink, J.J., van Doorn, A.J.: Representation of local geometry in the visual system. Biol. Cybern. 55(6), 367–375 (1987)

    Article  MathSciNet  MATH  Google Scholar 

  5. Lindeberg, T.: Scale-Space Theory in Computer Vision. Kluwer Academic Publishers, Berlin (1994)

    Book  MATH  Google Scholar 

  6. Marr, D.C., Hildreth, E.: Theory of edge detection. In: Proceedings of the Royal Society of London, vol. B-207, no. 1167, pp. 187–217. February 1980

    Google Scholar 

  7. Sonka, M., Hlavac, V., Boyle, R.: Image Processing Analysis, and Machine Vision, 2nd edn. PWS Publishing, Boston (1999)

    Google Scholar 

  8. Rao, A.R., Schunck, B.G.: Computing oriented texture fields. CVGIP: Graph. Models Image Process. 53(2), 157–185 (1991)

    Google Scholar 

  9. Weickert, J.: Coherence-enhancing diffusion filtering. Int. J. Comput. Vision 31(2/3), 111–127 (1999)

    Article  Google Scholar 

  10. Breiman, L.: Random forests. Mach. Learn. 45(1), 5–32 (2001)

    Article  MathSciNet  MATH  Google Scholar 

  11. Wang, C.-W., Gosno, E., Li, Y.: Fully automatic, robust 3D registration of serial-section microscopic images. Sci. Rep. 5, 15051 (2015)

    Article  Google Scholar 

Download references

Acknowledgments

Authors would like to thank the Ministry of Science and Technology of Taiwan under Grant No. MOST104-2221-E-011-085 for the financial support.

Author information

Authors and Affiliations

  1. Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei City, Taiwan

    Ching-Wei Wang & Jia-Hong Lee

Authors
  1. Ching-Wei Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jia-Hong Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ching-Wei Wang .

Editor information

Editors and Affiliations

  1. Istituto Italiano di Tecnologia (IIT), Genova, Italy

    Alessandro Crimi

  2. TU München, Computer Science, München, Germany

    Bjoern Menze

  3. Medical Informatics, University of Lübeck, Lübeck, Germany

    Oskar Maier

  4. Surgical Technology and Biomechanics, Universität Bern, Bern, Switzerland

    Mauricio Reyes

  5. Medical Informatics, University of Lübeck, Lübeck, Germany

    Heinz Handels

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this paper

Cite this paper

Wang, CW., Lee, JH. (2016). Stroke Lesion Segmentation of 3D Brain MRI Using Multiple Random Forests and 3D Registration. In: Crimi, A., Menze, B., Maier, O., Reyes, M., Handels, H. (eds) Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries. BrainLes 2015. Lecture Notes in Computer Science(), vol 9556. Springer, Cham. https://doi.org/10.1007/978-3-319-30858-6_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-30858-6_19

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30857-9

  • Online ISBN: 978-3-319-30858-6

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation