基于SIDWT和迭代自一致性的快速并行成像重建方法

Fast Parallel Imaging Reconstruction Method Based on SIDWT and Iterative Self-Consistency

为提高并行磁共振成像的重建速度,基于平移不变离散小波变换(SIDWT)和迭代自一致性并行成像重建(SPIRiT)模型,提出一种高效的重建方法fSIDWT-SPIRiT.该方法针对含有数据一致项、校正一致项和L1范数正则项的复杂优化问题,首先将数据一致项和校正一致项进行合并处理,之后利用快速投影迭代软阈值算法进行求解以实现快速并行磁共振成像重建.最后,在不同人体器官的数据集上进行测试.仿真实验结果表明:与其他方法相比,该方法能够在保证图像重建质量的同时,具有更快的收敛速度.

To improve the reconstruction speed of parallel magnetic resonance imaging,an efficient reconstruction method named fSIDWT-SPIRiT is proposed based on shift-invariant discrete wavelets transform(SIDWT)and the iterative self-consistent parallel imaging reconstruction(SPIRiT)model.This method addresses the complex optimization problem containing data consistency term,calibration consistency term,and L1-norm regularization term.First,data consistency term and calibration consistency term are combined and processed,and then solved by a projected fast iterative shrinkage-thresholding algorithm to achieve fast parallel MRI reconstruction.Finally,simulation experiments are conducted using different human organ datasets.The results show that the proposed method is able to guarantee the image reconstruction quality with a faster convergence speed compared with other methods.