Skip to main content

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

Abstract

In this work we review how the diffusivity profiles obtained from diffusion MRI can be expressed in terms of Cartesian tensors of ranks higher than 2. When the rank of the tensor being used is 2, one recovers traditional diffusion tensor imaging (DTI). Therefore our approach can be seen as a generalization of DTI. The properties of generalized diffusion tensors are discussed. The shortcomings of DTI experienced in the presence of orientational heterogeneity may cause inaccurate anisotropy values and incorrect fiber orientations. Employment of higher rank tensors is helpful in overcoming these difficulties.

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 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 109.99
Price excludes VAT (USA)
  • Durable hardcover 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. Basser P. J., Mattiello J., et al. (1994) MR diffusion tensor spectroscopy and imaging. Biophys. J. 66(1), 259–267.

    Article  Google Scholar 

  2. Basser P. J., Mattiello J., et al. (1994) Estimation of the effective self-diffusion tensor from the NMR spin echo. J. Magn. Reson. B 103(3), 247–254.

    Article  Google Scholar 

  3. Torrey H. C. (1956) Bloch equations with diffusion terms. Phys. Rev. 104(3), 563–565.

    Article  Google Scholar 

  4. Stejskal E. O., Tanner J. E. (1965) Spin diffusion measurements: Spin echoes in the presence of a time-dependent field gradient. J. Chem. Phys. 42(1), 288–292.

    Article  Google Scholar 

  5. Özarslan E., Mareci T. H. (2003) Generalized diffusion tensor imaging and analytical relationships between diffusion tensor imaging and high angular resolution diffusion imaging. Magn. Reson. Med. 50, 955–965.

    Article  Google Scholar 

  6. Schouten J. A. (1989) Tensor Analysis for Physicists. New York Dover Publications.

    Google Scholar 

  7. Dong Q., Welsh R. C., et al. (2004) Clinical applications of diffusion tensor imaging. J. Magn. Reson. Imaging 19(1), 6–18.

    Article  Google Scholar 

  8. Özarslan E., Vemuri B. C., et al. (2004) Generalized scalar measures for diffusion MRI using trace, variance and entropy. Magn. Reson. Med., accepted.

    Google Scholar 

  9. Basser P. J. (1995) Inferring microstructural features and the physiological state of tissues from diffusion-weighted images. NMR Biomed. 8, 333–344.

    Article  Google Scholar 

  10. Callaghan P. T. (1991) Principles of Nuclear Magnetic Resonance Microscopy. Oxford Clarendon Press.

    Google Scholar 

  11. Özarslan E., Vemuri B. C., et al. (2004) Multiple fiber orientations resolved by generalized diffusion tensor imaging. Proc. Intl. Soc. Mag. Reson. Med. 89.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2006 Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Özarslan, E., Vemuri, B.C., Mareci, T.H. (2006). Higher Rank Tensors in Diffusion MRI. In: Weickert, J., Hagen, H. (eds) Visualization and Processing of Tensor Fields. Mathematics and Visualization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-31272-2_10

Download citation

Publish with us

Policies and ethics