Abstract：
:Magnetic resonance parameter mapping (e.g., T1 mapping, T2 mapping, T*2 mapping) is a valuable tool for tissue characterization. However, its practical utility has been limited due to long data acquisition time. This paper addresses this problem with a new model-based parameter mapping method. The proposed method utilizes a formulation that integrates the explicit signal model with sparsity constraints on the model parameters, enabling direct estimation of the parameters of interest from highly undersampled, noisy k-space data. An efficient greedy-pursuit algorithm is described to solve the resulting constrained parameter estimation problem. Estimation-theoretic bounds are also derived to analyze the benefits of incorporating sparsity constraints and benchmark the performance of the proposed method. The theoretical properties and empirical performance of the proposed method are illustrated in a T2 mapping application example using computer simulations.
journal_name
IEEE Trans Med Imagingjournal_title
IEEE transactions on medical imagingauthors
Zhao B,Lam F,Liang ZPdoi
10.1109/TMI.2014.2322815subject
Has Abstractpub_date
2014-09-01 00:00:00pages
1832-44issue
9eissn
0278-0062issn
1558-254Xjournal_volume
33pub_type
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