Clark Darin P, Badea Cristian T
Center for In Vivo Microscopy, Department of Radiology, Duke University Medical Center, Durham, NC, United States of America.
PLoS One. 2017 Jul 6;12(7):e0180324. doi: 10.1371/journal.pone.0180324. eCollection 2017.
Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral separation on the order of the energy resolution of the PCD hardware.
当前的光子计数X射线探测器（PCD）技术面临着与光谱保真度和光子饥饿相关的限制。解决这些限制的一种策略是用能量积分探测器（EID）采集的高分辨率、低噪声数据来补充PCD数据。在这项工作中，我们提出了一种迭代的混合重建技术，该技术将PCD数据的光谱特性与EID数据的分辨率和信噪比特性相结合。我们的混合重建技术基于数据保真度的代数模型，该模型将EID数据代入与PCD重建相关的数据保真度项中，从而产生一个联合重建问题。在分裂Bregman框架内，这些数据保真度约束在对光谱秩以及在EID和PCD数据重建之间测量的联合强度梯度稀疏性的附加约束下被最小化。在推导了所提出的技术之后，我们将其应用于包含小动物微型CT中实际碘、钡和钙浓度的数字体模的重建。该实验结果表明，对于分别以176μm和254μm的固有空间分辨率（点扩散函数，半高宽）重建的EID和PCD数据，在2mm特征中，浓度≥5mg/ml的碘和浓度≥10mg/ml的钡能够可靠地分离和检测。此外，相对于仅使用PCD数据进行重建，混合重建被证明可以提高材料分解结果中的空间分辨率，并将低对比度可探测性提高多达2.6倍。模拟实验的参数基于在软组织肉瘤小鼠模型中进行的体内微型CT实验。从该体内数据产生的材料分解结果证明了以PCD硬件能量分辨率量级的光谱分离来区分两种K边造影剂的可行性。
