Chen Buxin, Zhang Zheng, Xia Dan, Sidky Emil Y, Gilat-Schmidt Taly, Pan Xiaochuan
Department of Radiology, The University of Chicago, Chicago, IL 60637, USA.
Department of Biomedical Engineering, Marquette University and Medical College of Wisconsin, Milwaukee, WI 53201, USA.
Bioengineering (Basel). 2022 Dec 6;9(12):775. doi: 10.3390/bioengineering9120775.
Dual-energy CT (DECT) with scans over limited-angular ranges (LARs) may allow reductions in scan time and radiation dose and avoidance of possible collision between the moving parts of a scanner and the imaged object. The beam-hardening (BH) and LAR effects are two sources of image artifacts in DECT with LAR data. In this work, we investigate a two-step method to correct for both BH and LAR artifacts in order to yield accurate image reconstruction in DECT with LAR data. From low- and high-kVp LAR data in DECT, we first use a data-domain decomposition (DDD) algorithm to obtain LAR basis data with the non-linear BH effect corrected for. We then develop and tailor a directional-total-variation (DTV) algorithm to reconstruct from the LAR basis data obtained basis images with the LAR effect compensated for. Finally, using the basis images reconstructed, we create virtual monochromatic images (VMIs), and estimate physical quantities such as iodine concentrations and effective atomic numbers within the object imaged. We conduct numerical studies using two digital phantoms of different complexity levels and types of structures. LAR data of low- and high-kVp are generated from the phantoms over both single-arc (SA) and two-orthogonal-arc (TOA) LARs ranging from 14∘ to 180∘. Visual inspection and quantitative assessment of VMIs obtained reveal that the two-step method proposed can yield VMIs in which both BH and LAR artifacts are reduced, and estimation accuracy of physical quantities is improved. In addition, concerning SA and TOA scans with the same total LAR, the latter is shown to yield more accurate images and physical quantity estimations than the former. We investigate a two-step method that combines the DDD and DTV algorithms to correct for both BH and LAR artifacts in image reconstruction, yielding accurate VMIs and estimations of physical quantities, from low- and high-kVp LAR data in DECT. The results and knowledge acquired in the work on accurate image reconstruction in LAR DECT may give rise to further understanding and insights into the practical design of LAR scan configurations and reconstruction procedures for DECT applications.
具有有限角度范围（LAR）扫描的双能CT（DECT）可能会减少扫描时间和辐射剂量，并避免扫描仪的移动部件与成像对象之间可能发生的碰撞。束硬化（BH）和LAR效应是具有LAR数据的DECT中图像伪影的两个来源。在这项工作中，我们研究了一种两步法来校正BH和LAR伪影，以便在具有LAR数据的DECT中实现准确的图像重建。从DECT中的低千伏峰值和高千伏峰值LAR数据出发，我们首先使用数据域分解（DDD）算法来获得校正了非线性BH效应的LAR基数据。然后，我们开发并定制了一种方向全变差（DTV）算法，以从获得的LAR基数据中重建补偿了LAR效应的基图像。最后，使用重建的基图像，我们创建虚拟单色图像（VMI），并估计成像对象内的碘浓度和有效原子序数等物理量。我们使用两个具有不同复杂程度和结构类型的数字体模进行了数值研究。低千伏峰值和高千伏峰值的LAR数据是从体模在14°至180°的单弧（SA）和双正交弧（TOA）LAR上生成的。对获得的VMI进行目视检查和定量评估表明，所提出的两步法可以生成减少了BH和LAR伪影的VMI，并提高了物理量的估计精度。此外，对于具有相同总LAR的SA和TOA扫描，结果表明后者比前者能产生更准确的图像和物理量估计。我们研究了一种结合DDD和DTV算法的两步法，以校正图像重建中的BH和LAR伪影，从DECT中的低千伏峰值和高千伏峰值LAR数据中生成准确的VMI和物理量估计。在LAR DECT中准确图像重建工作中获得的结果和知识可能会进一步加深对LAR扫描配置和DECT应用重建程序实际设计的理解和认识。
