Abstract
A method for regularizing diffusion tensor magnetic resonance images (DT-MRI) is presented. The scheme is divided into two main parts: a restoration of the principal diffusion direction, and a regularization of the 3 eigenvalue maps. The former make use of recent variational methods for restoring direction maps, while the latter makes use of the strong structural information embedded in the diffusion tensor image to drive a non-linear anisotropic diffusion process. The whole process is illustrated on synthetic and real data, and possible improvements are discussed.
Acknowledgements
OC is funded by the Wellcome Trust. Images were kindly provided by Geoff Parker, Imaging Science and Biomedical Engineering, University of Manchester, and the NMR research unit of the Institute of Neurology, London. All 3D renderings were done using the Visualisation Toolkit (VTK - http://www.kitware.com).
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Coulon, O., Alexander, D.C., Arridge, S.R. (2001). A Regularization Scheme for Diffusion Tensor Magnetic Resonance Images. 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_8
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DOI: https://doi.org/10.1007/3-540-45729-1_8
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