To understand evolving pathology in the central nervous system (CNS) and develop effective treatments, it is essential to correlate the nerve fiber connectivity with the visualization of function. Diffusion tensor imaging (DTI) can provide the fundamental information required for viewing structural connectivity. We present a novel algorithm for automatic fiber tract mapping in the CNS specifically, the spinal cord. The automatic fiber tract mapping problem is solved in two phases, namely a data smoothing phase and a fiber tract mapping phase. In the former, smoothing is achieved via a new weighted total variation (TV)-norm minimization (for vector-valued data) which strives to smooth while retaining all relevant detail. For the fiber tract mapping, a smooth 3D vector field indicating the dominant anisotropic direction at each spatial location is computed from the smoothed data. Fiber tracts are then determined as the smooth integral curves of this vector field in a variational framework.


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    Titel :

    Fiber tract mapping from diffusion tensor MRI


    Beteiligte:
    Vemuri, B.C. (Autor:in) / Chen, Y. (Autor:in) / Rao, M. (Autor:in) / McGraw, T. (Autor:in) / Wang, Z. (Autor:in) / Mareci, T. (Autor:in)


    Erscheinungsdatum :

    2001-01-01


    Format / Umfang :

    889125 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Fiber Tract Mapping from Diffusion Tensor MRI

    Vemuri, B. / Chen, Y. / Rao, M. et al. | British Library Conference Proceedings | 2001


    Simultaneous Smoothing and Estimation of the Tensor Field from Diffusion Tensor MRI

    Wang, Z. / Vemuri, B. / Chen, Y. et al. | British Library Conference Proceedings | 2003



    Registration of Diffusion Tensor Images

    Zhang, H. / Yushkevich, P. / Gee, J. et al. | British Library Conference Proceedings | 2004


    Registration of diffusion tensor images

    Hui Zhang, / Yushkevich, P.A. / Gee, J.C. | IEEE | 2004