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Distributed Anatomical Brain Connectivity Derived from Diffusion Tensor Imaging

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Information Processing in Medical Imaging (IPMI 2001)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2082))

Abstract

A method is presented for determining likely paths of anatomical connection between regions of the brain using MR diffusion tensor information. Level set theory, applied using fast marching methods, is used to generate 3-D time of arrival maps, from which connection paths between brain regions may be identified. The method is demonstrated in the normal brain and it is shown that major white matter tracts may be elucidated and that multiple connections and tract branching are allowed. Maps of the likelihood of connection between brain regions are also determined. Two metrics are described for estimating the (informal) likelihood of connection between regions.

Acknowledgements

This work was supported by the Multiple Sclerosis Society of Great Britain and Northern Ireland. The contributions of Klaas Stephan, Olga Ciccarelli, Sofia Eriksson, David Werring, and Olivier Coulon are gratefully acknowledged.

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Authors and Affiliations

  1. NMR Research Unit, University Department of Clinical Neurology, Institute of Neurology, University College London, Queen Square, London, WC1N 3BG, UK

    Geoffrey J.M. Parker & Gareth J. Barker

  2. Imaging Science and Biomedical Engineering, University of Manchester, Oxford Road, Manchester, M13 9PT, UK

    Geoffrey J.M. Parker

Authors
  1. Geoffrey J.M. Parker
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  2. 1]Claudia A.M. Wheeler-Kingshott
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  3. Gareth J. Barker
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Editor information

Editors and Affiliations

  1. Biomedical Engineering, University of California, One Shields Avenue, Davis, CA, 95616, USA

    Michael F. Insana

  2. Signal and Image Processing Institute, University of Southern California, 3740 McClintock Avenue, Los Angeles, CA, 90089-2564, USA

    Richard M. Leahy

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© 2001 Spinger-Verlag Berlin Heidelberg

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Parker, G.J., Wheeler-Kingshott, 1.A., Barker, G.J. (2001). Distributed Anatomical Brain Connectivity Derived from Diffusion Tensor Imaging. In: Insana, M.F., Leahy, R.M. (eds) Information Processing in Medical Imaging. IPMI 2001. Lecture Notes in Computer Science, vol 2082. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45729-1_9

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  • DOI: https://doi.org/10.1007/3-540-45729-1_9

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-42245-7

  • Online ISBN: 978-3-540-45729-9

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