Multi-exponential analysis of magnitude MR images using a quantitative multispectral edge-preserving filter.
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.
Bonny
Jean Marie
JM
INRA Unité STIM, Centre de Theix, 63122 Saint-Genès Champanelle, France. bonny@clermont.inra.fr
Boespflug-Tanguly
Odile
O
Zanca
Michel
M
Renou
Jean Pierre
JP
D000465:Algorithms; D001921:Brain / Q000033:anatomy & histology*; D006801:Humans; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008953:Models, Anatomic; D012815:Signal Processing, Computer-Assisted