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Neural Tractography Using an Unscented Kalman Filter

  • Conference paper
Information Processing in Medical Imaging (IPMI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5636))

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Abstract

We describe a technique to simultaneously estimate a local neural fiber model and trace out its path. Existing techniques estimate the local fiber orientation at each voxel independently so there is no running knowledge of confidence in the estimated fiber model. We formulate fiber tracking as recursive estimation: at each step of tracing the fiber, the current estimate is guided by the previous. To do this we model the signal as a mixture of Gaussian tensors and perform tractography within a filter framework. Starting from a seed point, each fiber is traced to its termination using an unscented Kalman filter to simultaneously fit the local model and propagate in the most consistent direction. Despite the presence of noise and uncertainty, this provides a causal estimate of the local structure at each point along the fiber. Synthetic experiments demonstrate that this approach reduces signal reconstruction error and significantly improves the angular resolution at crossings and branchings. In vivo experiments confirm the ability to trace out fibers in areas known to contain such crossing and branching while providing inherent path regularization.

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Author information

Authors and Affiliations

  1. Psychiatry Neuroimaging Laboratory, Harvard Medical School, Boston, MA, USA

    James G. Malcolm, Martha E. Shenton & Yogesh Rathi

  2. Brockton Division, VA Boston Healthcare System, Brockton, MA, USA

    Martha E. Shenton

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  1. James G. Malcolm
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  2. Martha E. Shenton
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  3. Yogesh Rathi
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 North Charles Street, MD 21218, Baltimore, USA

    Jerry L. Prince

  2. Department of Radiology, Johns Hopkins University, 600 North Wolfe Street, MD 21287, Baltimore, USA

    Dzung L. Pham

  3. Division of Imaging and Applied Mathematics, OSEL, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, MD 20993, Silver Spring, USA

    Kyle J. Myers

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© 2009 Springer-Verlag Berlin Heidelberg

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Malcolm, J.G., Shenton, M.E., Rathi, Y. (2009). Neural Tractography Using an Unscented Kalman Filter. In: Prince, J.L., Pham, D.L., Myers, K.J. (eds) Information Processing in Medical Imaging. IPMI 2009. Lecture Notes in Computer Science, vol 5636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02498-6_11

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  • DOI: https://doi.org/10.1007/978-3-642-02498-6_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02497-9

  • Online ISBN: 978-3-642-02498-6

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