Abstract
The empirical origin of random noise is described, its influence on DTI variables is illustrated by a review of numerical and in vivo studies supplemented by new simulations investigating high noise levels. A stochastic model of noise propagation is presented to structure noise impact in DTI. Finally, basics of voxelwise and spatial denoising procedures are presented. Recent denoising procedures are reviewed and consequences of the stochastic model for convenient denoising strategies are discussed.
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Hahn, K.R., Prigarin, S., Heim, S., Hasan, K. (2006). Random Noise in Diffusion Tensor Imaging, its Destructive Impact and Some Corrections. 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_6
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DOI: https://doi.org/10.1007/3-540-31272-2_6
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