Shen Yusong, Zhang Liwen, Shang Yaxin, Jia Guang, Yin Lin, Zhang Hui, Tian Jie, Yang Guanyu, Hui Hui
School of Computer Science and Engineering, Southeast University, Nanjing, People's Republic of China.
CAS Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, People's Republic of China.
Phys Med Biol. 2023 Dec 11;68(24). doi: 10.1088/1361-6560/ad078d.
. Real-time reconstruction of magnetic particle imaging (MPI) shows promising clinical applications. However, prevalent reconstruction methods are mainly based on serial iteration, which causes large delay in real-time reconstruction. In order to achieve lower latency in real-time MPI reconstruction, we propose a parallel method for accelerating the speed of reconstruction methods.. The proposed method, named adaptive multi-frame parallel iterative method (AMPIM), enables the processing of multi-frame signals to multi-frame MPI images in parallel. To facilitate parallel computing, we further propose an acceleration strategy for parallel computation to improve the computational efficiency of our AMPIM.. OpenMPIData was used to evaluate our AMPIM, and the results show that our AMPIM improves the reconstruction frame rate per second of real-time MPI reconstruction by two orders of magnitude compared to prevalent iterative algorithms including the Kaczmarz algorithm, the conjugate gradient normal residual algorithm, and the alternating direction method of multipliers algorithm. The reconstructed image using AMPIM has high contrast-to-noise with reducing artifacts.. The AMPIM can parallelly optimize least squares problems with multiple right-hand sides by exploiting the dimension of the right-hand side. AMPIM has great potential for application in real-time MPI imaging with high imaging frame rate.
磁粒子成像(MPI)的实时重建显示出良好的临床应用前景。然而,现有的重建方法主要基于串行迭代,这导致实时重建中存在较大延迟。为了在实时MPI重建中实现更低的延迟,我们提出了一种并行方法来加速重建方法的速度。所提出的方法名为自适应多帧并行迭代方法(AMPIM),它能够并行处理多帧信号以生成多帧MPI图像。为了便于并行计算,我们进一步提出了一种并行计算加速策略,以提高AMPIM的计算效率。使用OpenMPIData对我们的AMPIM进行评估,结果表明,与包括卡兹马尔兹算法、共轭梯度法和交替方向乘子法在内的现有迭代算法相比,我们的AMPIM将实时MPI重建的每秒重建帧率提高了两个数量级。使用AMPIM重建的图像具有高对比度噪声比且伪影减少。AMPIM可以通过利用右侧的维度并行优化具有多个右侧项的最小二乘问题。AMPIM在高成像帧率的实时MPI成像中具有巨大的应用潜力。
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