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Multi-exponential analysis of magnitude MR images using a quantitative multispectral edge-preserving filter
Jean Marie Bonny1, Odile Boespflug-Tanguly, Michel Zanca
1INRA Unité STIM, Centre de Theix, 63122 Saint-Genès Champanelle, France. bonny@clermont.inra.fr
Abstract:
A solution for discrete multi-exponential analysis of T(2) relaxation decay curves obtained in current multi-echo imaging protocol conditions is described. We propose a preprocessing step to improve the signal-to-noise ratio and thus lower the signal-to-noise ratio threshold from which a high percentage of true multi-exponential detection is detected. It consists of a multispectral nonlinear edge-preserving filter that takes into account the signal-dependent Rician distribution of noise affecting magnitude MR images. Discrete multi-exponential decomposition, which requires no a priori knowledge, is performed by a non-linear least-squares procedure initialized with estimates obtained from a total least-squares linear prediction algorithm. This approach was validated and optimized experimentally on simulated data sets of normal human brains.

