Weighted total variation using split Bregman fast quantitative susceptibility mapping reconstruction method

• 来源期刊: 中国物理B（英文版）
• 关键词: quantitative susceptibility mapping ill-posed inverse problem noise-suppressed data weighting split Bregman iteration
• 年，卷（期）: 2018,（8）
• 页码范围: 655-664
• 页数: 10页
• 语种: 英文
• DOI: 10.1088/1674-1056/27/8/088701

摘要

An ill-posed inverse problem in quantitative susceptibility mapping (QSM) is usually solved using a regularization and optimization solver, which is time consuming considering the three-dimensional volume data. However, in clinical diagnosis, it is necessary to reconstruct a susceptibility map efficiently with an appropriate method. Here, a modified QSM reconstruction method called weighted total variation using split Bregman (WTVSB) is proposed. It reconstructs the susceptibility map with fast computational speed and effective artifact suppression by incorporating noise-suppressed data weighting with split Bregman iteration. The noise-suppressed data weighting is determined using the Laplacian of the calculated local field, which can prevent the noise and errors in field maps from spreading into the susceptibility inversion. The split Bregman iteration accelerates the solution of the L1-regularized reconstruction model by utilizing a preconditioned conjugate gradient solver. In an experiment, the proposed reconstruction method is compared with truncated k-space division (TKD), morphology enabled dipole inversion (MEDI), total variation using the split Bregman (TVSB) method for numerical simulation, phantom and in vivo human brain data evaluated by root mean square error and mean structure similarity. Experimental results demonstrate that our proposed method can achieve better balance between accuracy and efficiency of QSM reconstruction than conventional methods, and thus facilitating clinical applications of QSM.