Changwei Hu1, Xiaobo Qu2, Di Guo2,
Lijun Bao1, Shuhui Cai1, Zhong Chen1
1Department of Physics,
Xiamen University, Xiamen, Fujian, China, People's Republic of; 2Department
of Communication Engineering, Xiamen University, Xiamen, Fujian, China,
People's Republic of
Undersampling k-space is an effective way to reduce acquisition time for MRI. However, aliasing artifacts introduced by undersampling may blur the edges of MR images, which often contain important information for clinical diagnosis. In this work, we propose an edge-weighted model by pluging two weighting matrix into the objective function of constrained l1 norm minimization problem. Reconstructions with more precise edge recovery are then obtained by the proposed EWIT algorithm.
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