Shuai Huang1, James J. Lah1, Jason W. Allen1, and Deqiang Qiu1
1Emory University, Atlanta, GA, United States
1Emory University, Atlanta, GA, United States
T2* mapping is performed from undersampled measurements using a Bayesian approach where the parameters are automatically and adaptively estimated. It is more efficient and outperforms state-of-the-art regularization-based approaches, especially in the low-sampling-rate regime.
Figure 1: The factor graph of the proposed nonlinear AMP framework for T2* mapping, the circle represents the variable node, and the black square represents the factor node.
Figure 3: Sampling rate = 10%. The recovered T2* map, proton density and their corresponding relative error images using different approaches.
