计算机工程与应用2018，Vol.54Issue(8)：28-35,8.DOI:10.3778/j.issn.1002-8331.1801-0104
磁共振图像的原始-对偶近似迭代重建算法
Proximal iterative reconstruction algorithm for MR images based on primal-dual framework
摘要
Abstract
Compressed Sensing(CS)based Magnetic Resonance Imaging(MRI)is a fast imaging technology which exploits the sparsity of Magnetic Resonance(MR)images.In view of the linear composite regularization term in the canonic reconstruction model for CS-MRI,a primal-dual iterative reconstruction algorithm is proposed which solves aug-mented Lagrangian of the primal and dual problems iteratively. The Moreau envelope is utilized to cope with the non-smooth regularization terms followed by a gradient calculation step using the approximate operator.Experiment results of phantom and real MR images show that compared with Conjugate Gradient algorithm(CG),operator splitting algorithm (TVCMRI),variable splitting algorithm(RecPF)and fast composite splitting algorithm(FCSA),the algorithm gives the best reconstruction effect.In addition,the algorithm complexity compares favorably with FCSA which is the fastest algo-rithm so far.关键词
快速磁共振成像/压缩感知/原始-对偶/近似算子Key words
fast magnetic resonance imaging/compressed sensing/primal-dual/approximate operator分类
信息技术与安全科学引用本文复制引用
刘晓晖,张鑫媛,路利军,冯前进,陈武凡..磁共振图像的原始-对偶近似迭代重建算法[J].计算机工程与应用,2018,54(8):28-35,8.基金项目
国家自然科学基金(No.81501541,No.81601564) （No.81501541,No.81601564）
国家重点研发专项(No.2016YFC0104003). （No.2016YFC0104003）
