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Optimal Regularization for MR Diffusion Signal Reconstruction
Abstract : In this paper we address two problems related to the parametric reconstruction of the diffusion signal in the complete 3D Q-space. We propose a modified Spherical Polar Fourier (mSPF) basis to naturally impose the continuity of the diffusion signal on the whole space. This mathematical constraint results in a dimension reduction with respect to the original SPF basis. In addition, we derive the expression of a Laplace regularization operator in this basis, and compute optimal regularization weight using generalized cross validation (GCV). Experiments on synthetic and real data show that this regularization leads to a more accurate reconstruction than the commonly used low-pass filters.
Cited literature [11 references]
https://hal.inria.fr/hal-00660635
Contributor : Emmanuel Caruyer <>
Submitted on : Tuesday, January 17, 2012 - 11:17:51 AM
Last modification on : Thursday, November 26, 2020 - 4:52:04 PM
Long-term archiving on: : Monday, November 19, 2012 - 1:50:28 PM
Contributor : Emmanuel Caruyer <>
Submitted on : Tuesday, January 17, 2012 - 11:17:51 AM
Last modification on : Thursday, November 26, 2020 - 4:52:04 PM
Long-term archiving on: : Monday, November 19, 2012 - 1:50:28 PM
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