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Fast trajectory-independent model-based reconstruction algorithm for multi-dimensional magnetic particle imaging

计算机科学 算法 反褶积 迭代重建 阈值 重建算法 工件(错误) 计算机视觉 人工智能 校准 扫描仪 磁粉成像 断层重建 信号(编程语言) 利萨茹曲线 振铃人工制品 修边 测距 切趾 探测器 图像处理 点(几何) 三维重建 合成数据 曲面重建 平滑的 信号重构 噪音(视频) 点扩散函数
作者
Vladyslav Gapyak,Thomas März,Andreas Weinmann
出处
期刊:Physics in Medicine and Biology [IOP Publishing]
卷期号:70 (23): 235028-235028 被引量:1
标识
DOI:10.1088/1361-6560/ae205c
摘要

Abstract Objective. Magnetic particle imaging (MPI) is a tomographic technique for visualizing the spatio-temporal distribution of superparamagnetic nanoparticles, with applications ranging from cancer detection to real-time cardiovascular monitoring. Traditional MPI reconstruction relies on either time-consuming calibration (measured system matrix) or model-based simulation of the forward operator. Recent developments have shown the applicability of a Chebyshev-polynomial-based method to multi-dimensional Lissajous field-free point (FFP) scans. This method is bound to the particular choice of sinusoidal scanning trajectories. In this paper, we present a working reconstruction pipeline—the MoBiT-2S—that achieves reconstruction on real 2D MPI data, performed with a trajectory-independent model-based reconstruction algorithm based on a reconstruction formula. Approach. We employ a model-based two-stage algorithm to reconstruct the particle concentration from the scanning data, thereby realizing a reconstruction formula. In the first (core) stage the MPI core response is reconstructed from the signal using a variational formulation; in the second (deconvolution) stage, the trace of the core response is deconvolved to obtain the final reconstruction. Main results. We further develop our methodological approach to make the reconstruction-formula-based algorithm work on real 2D MPI data. In particular, we further develop a zero-shot plug-and-play algorithm to address the deconvolution problem represented by the reconstruction formula. Further contributions of MoBiT-2S include channel-specific thresholding of the input data and per-iteration percentile trimming for artifact reduction. We evaluate MoBiT-2S on the ‘MPIData: equilibrium model with anisotropy’ dataset, featuring 2D FFP scans acquired using a Bruker preclinical scanner. We quantitatively and qualitatively compare our reconstructions with state-of-the-art approaches. In addition, we perform reconstructions on data from a 2D MPI scanner which does not employ a Lissajous scanning sequence. Significance. MoBiT-2S exhibits competitive reconstruction capabilities across different scanning scenarios on real MPI data, with Lissajous and non-Lissajous scans, and partial data, showing the potential of the proposed method for general-purpose, flexible model-based MPI reconstruction.
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