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首页> 外文期刊>IEEE Transactions on Medical Imaging >A Spectral CT Method to Directly Estimate Basis Material Maps From Experimental Photon-Counting Data
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A Spectral CT Method to Directly Estimate Basis Material Maps From Experimental Photon-Counting Data

机译：从实验光子计数数据直接估算基础材料图的光谱CT方法

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摘要

The proposed spectral CT method solves the constrained one-step spectral CT reconstruction (cOSSCIR) optimization problem to estimate basis material maps while modeling the nonlinear X-ray detection process and enforcing convex constraints on the basis map images. In order to apply the optimization-based reconstruction approach to experimental data, the presented method empirically estimates the effective energy-window spectra using a calibration procedure. The amplitudes of the estimated spectra were further optimized as part of the reconstruction process to reduce ring artifacts. A validation approach was developed to select constraint parameters. The proposed spectral CT method was evaluated through simulations and experiments with a photon-counting detector. Basis material map images were successfully reconstructed using the presented empirical spectral modeling and cOSSCIR optimization approach. In simulations, the cOSSCIR approach accurately reconstructed the basis map images (<;1% error). In experiments, the proposed method estimated the low-density polyethylene region of the basis maps with 0.5% error in the PMMA image and 4% error in the aluminum image. For the Teflon region, the experimental results demonstrated 8% and 31% error in the PMMA and aluminum basis material maps, respectively, compared with -24% and 126% error without estimation of the effective energy window spectra, with residual errors likely due to insufficient modeling of detector effects. The cOSSCIR algorithm estimated the material decomposition angle to within 1.3 degree error, where, for reference, the difference in angle between PMMA and muscle tissue is 2.1 degrees. The joint estimation of spectral-response scaling coefficients and basis material maps was found to reduce ring artifacts in both a phantom and tissue specimen. The presented validation procedure demonstrated feasibility for the automated determination of algorithm constraint parameters.
机译：所提出的光谱CT方法解决了受限的一步式光谱CT重建（cOSSCIR）优化问题，从而在对非线性X射线检测过程进行建模并在基础图图像上实施凸约束的同时估算了基础材料图。为了将基于优化的重建方法应用于实验数据，提出的方法使用校准程序凭经验估算有效的能量窗口光谱。作为重建过程的一部分，可以进一步优化估计频谱的幅度，以减少环伪影。开发了一种验证方法来选择约束参数。通过使用光子计数检测器的仿真和实验对提出的光谱CT方法进行了评估。使用提出的经验光谱建模和cOSSCIR优化方法成功地重建了基础材料图图像。在仿真中，cOSSCIR方法可准确地重建基本图图像（误差小于1％）。在实验中，提出的方法估计了底图的低密度聚乙烯区域，PMMA图像的误差为0.5％，铝图像的误差为4％。对于特氟隆地区，实验结果表明，在PMMA和铝基材料图中，误差分别为8％和31％，而没有估算有效能窗光谱的误差为-24％和126％，残留误差可能是由于探测器效果建模不足。 cOSSCIR算法估计的材料分解角度误差在1.3度以内，作为参考，PMMA和肌肉组织之间的角度差为2.1度。发现光谱响应缩放系数和基础材料图的联合估计可以减少幻影和组织标本中的环伪影。提出的验证程序证明了自动确定算法约束参数的可行性。

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