In this study, we propose a linearized proximal alternating direction method with variable stepsize for solving total variation image reconstruction problems. Our method uses a linearized technique and the proximal fu...In this study, we propose a linearized proximal alternating direction method with variable stepsize for solving total variation image reconstruction problems. Our method uses a linearized technique and the proximal function such that the closed form solutions of the subproblem can be easily derived.In the subproblem, we apply a variable stepsize, that is like Barzilai-Borwein stepsize, to accelerate the algorithm. Numerical results with parallel magnetic resonance imaging demonstrate the efficiency of the proposed algorithm.展开更多
The relatively long scan time is still a bottleneck for both clinical applications and research of magnetic resonance imaging. To reduce the data acquisition time, we propose a novel fast magnetic resonance imaging me...The relatively long scan time is still a bottleneck for both clinical applications and research of magnetic resonance imaging. To reduce the data acquisition time, we propose a novel fast magnetic resonance imaging method based on parallel variable-density spiral acquisition, which combines undersampling optimization and nonlocal total variation reconstruction. The undersampling optimization promotes the incoherence of resultant aliasing artifact via the ＂worst-case＂ residual error metric, and thus accelerates the data acquisition. Moreover, nonlocal total variation reconstruction is utilized to remove such an incoherent aliasing artifact and so improve image quality. The feasibility of the proposed method is demonstrated by both numerical phantom simulation and in vivo experiment. The experimental results show that the proposed method can achieve high acceleration factor and effectively remove an aliasing artifact from data undersampling with well-preserved image details. The image quality is better than that achieved with the total variation method.展开更多
基金supported in part by the National Natural Science Foundation of China(11361018,11461015)Guangxi Natural Science Foundation(2014GXNSFFA118001)+3 种基金Guangxi Key Laboratory of Automatic Detecting Technology and Instruments(YQ15112,YQ16112)Guilin Science and Technology Project(20140127-2)the Innovation Project of Guangxi Graduate Education and Innovation Project of GUET Graduate Education(YJCXB201502)Guangxi Key Laboratory of Cryptography and Information Security(GCIS201624)
文摘In this study, we propose a linearized proximal alternating direction method with variable stepsize for solving total variation image reconstruction problems. Our method uses a linearized technique and the proximal function such that the closed form solutions of the subproblem can be easily derived.In the subproblem, we apply a variable stepsize, that is like Barzilai-Borwein stepsize, to accelerate the algorithm. Numerical results with parallel magnetic resonance imaging demonstrate the efficiency of the proposed algorithm.
基金Project supported by the National Natural Science Foundation of China(Grant Nos.81101030 and 61271132)
文摘The relatively long scan time is still a bottleneck for both clinical applications and research of magnetic resonance imaging. To reduce the data acquisition time, we propose a novel fast magnetic resonance imaging method based on parallel variable-density spiral acquisition, which combines undersampling optimization and nonlocal total variation reconstruction. The undersampling optimization promotes the incoherence of resultant aliasing artifact via the ＂worst-case＂ residual error metric, and thus accelerates the data acquisition. Moreover, nonlocal total variation reconstruction is utilized to remove such an incoherent aliasing artifact and so improve image quality. The feasibility of the proposed method is demonstrated by both numerical phantom simulation and in vivo experiment. The experimental results show that the proposed method can achieve high acceleration factor and effectively remove an aliasing artifact from data undersampling with well-preserved image details. The image quality is better than that achieved with the total variation method.
文摘目的磁共振并行采集技术(integrated parallel acquisition technique,iPAT)是磁共振快速采集技术,已广泛应用于临床,但对图像质量的影响国内还没有文献报导。文中探讨iPAT与常规采集技术对图像质量的影响。方法利用颈部矩阵线圈对1个体模及10名健康志愿者颈椎分别采用信号平均次数(number of signal averaged,NSA)为1次的常规扫描(常规/1次)及并行采集加速因子为2的iPAT(GRAPPA/1次)与NSA为2次并行采集加速因子为2的iPAT(GRAPPA/2次)的方法进行扫描,综合定量分析获得图像的信噪比(signal-to-noise ratio,SNR)、不均匀性。结果保持其他参数不变的情况下,GRAPPA/2次获得的图像质量、信噪比均高于其他两者平均次数为1次的扫描方法,但GRAPPA/1次扫描时间最短。结论合理选用平均次数及并行采集因子在保持扫描时间基本不变的情况下可显著提高图像质量,另外,在平均次数一定的情况下iPAT能大幅缩短成像时间,但图像质量会有所降低。
