Chen Buxin, Zhang Zheng, Xia Dan, Sidky Emil Y, Pan Xiaochuan
Department of Radiology, The University of Chicago, Chicago, IL 60637, USA.
Department of Radiology, The University of Chicago, Chicago, IL 60637, USA; Department of Radiation and Cellular Oncology, The University of Chicago, Chicago, IL 60637, USA.
Med Image Anal. 2024 Jan;91:103025. doi: 10.1016/j.media.2023.103025. Epub 2023 Nov 7.
Image reconstruction from data collected over full-angular range (FAR) in dual-energy CT (DECT) is well-studied. There exists interest in DECT with advanced scan configurations in which data are collected only over limited-angular ranges (LARs) for meeting unique workflow needs in certain practical imaging applications, and thus in the algorithm development for image reconstruction from such LAR data. The objective of the work is to investigate and prototype image reconstructions in DECT with LAR scans. We investigate and prototype optimization programs with various designs of constraints on the directional-total-variations (DTVs) of virtual monochromatic images and/or basis images, and derive the DTV algorithms to numerically solve the optimization programs for achieving accurate image reconstruction from data collected in a slew of different LAR scans. Using simulated and real data acquired with low- and high-kV spectra over LARs, we conduct quantitative studies to demonstrate and evaluate the optimization programs and their DTV algorithms developed. As the results of the numerical studies reveal, while the DTV algorithms yield images of visual quality and quantitative accuracy comparable to that of the existing algorithms from FAR data, the former reconstruct images with improved visualization, reduced artifacts, and also enhanced quantitative accuracy when applied to LAR data in DECT. Optimization-based, one-step algorithms, including the DTV algorithms demonstrated, can be developed for quantitative image reconstruction from spectral data collected over LARs of extents that are considerably smaller than the FAR in DECT. The theoretical and numerical results obtained can be exploited for prototyping designs of optimization-based reconstructions and LAR scans in DECT, and they may also yield insights into the development of reconstruction procedures in practical DECT applications. The approach and algorithms developed can naturally be applied to investigating image reconstruction from LAR data in multi-spectral and photon-counting CT.
双能CT（DECT）中基于全角范围（FAR）采集数据的图像重建已得到充分研究。对于具有先进扫描配置的DECT存在一定兴趣，在这种配置中，仅在有限角范围（LAR）内采集数据以满足某些实际成像应用中的独特工作流程需求，因此也对基于此类LAR数据进行图像重建的算法开发感兴趣。这项工作的目标是研究和开发DECT中LAR扫描的图像重建原型。我们研究并开发了具有各种设计的优化程序，这些程序对虚拟单色图像和/或基图像的方向总变分（DTV）施加约束，并推导DTV算法以数值求解优化程序，从而从一系列不同LAR扫描中采集的数据实现准确的图像重建。使用在LAR上以低千伏和高千伏光谱采集的模拟数据和真实数据，我们进行定量研究以演示和评估所开发的优化程序及其DTV算法。数值研究结果表明，虽然DTV算法生成的图像在视觉质量和定量准确性方面与基于FAR数据的现有算法相当，但前者在应用于DECT中的LAR数据时，能够重建出可视化效果更好、伪影减少且定量准确性更高的图像。可以开发基于优化的一步算法，包括所演示的DTV算法，用于从DECT中比FAR小得多的LAR范围内采集的光谱数据进行定量图像重建。所获得的理论和数值结果可用于DECT中基于优化的重建和LAR扫描的原型设计，并且它们还可能为实际DECT应用中重建程序的开发提供见解。所开发的方法和算法自然可应用于研究多光谱和光子计数CT中基于LAR数据的图像重建。
