Hybrid Weighted l(1)-Total Variation Constrained Reconstruction for MR Image

作者：Zhao Di; Du Huiqian^*; Mei Wenbo

来源：Chinese Journal of Electronics, 2014, 23(4): 747-752.

• Compressed sensing (CS)
• Magnetic resonance imaging (MRI)
• Image reconstruction
• Weighted l(1) norm
• Weighted Total variation (TV)

Compressed sensing based Magnetic resonance (MR) image reconstruction can be done by minimizing the sum of least square data fitting item, the Total variation (TV) and l(1) norm regularizations. In this paper, inspired by the conventional constrained reconstruction model, we propose a hybrid weighted l(1)-TV minimization method to reconstruct MR image. We introduce the iterative mechanism to update the weights for l(1) and TV norms adaptively. The weights vary at each element of the image matrix according to the presented weights selection strategy. Experiments on Shepp-Logan phantom and practical MR images demonstrate the proposed method can preserve image details and obtain improved reconstruction quality compared to the traditional CS-MRI method and other weighted methods.

• 出版日期2014-10
• 单位北京理工大学