A dual-energy CT reconstruction method based on anchor network from dual quarter scans.

IF 1.7 3区 医学 Q3 INSTRUMENTS & INSTRUMENTATION Journal of X-Ray Science and Technology Pub Date : 2024-01-01 DOI:10.3233/XST-230245
Junru Ren, Wenkun Zhang, YiZhong Wang, Ningning Liang, Linyuan Wang, Ailong Cai, Shaoyu Wang, Zhizhong Zheng, Lei Li, Bin Yan
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Abstract

Compared with conventional single-energy computed tomography (CT), dual-energy CT (DECT) provides better material differentiation but most DECT imaging systems require dual full-angle projection data at different X-ray spectra. Relaxing the requirement of data acquisition is an attractive research to promote the applications of DECT in wide range areas and reduce the radiation dose as low as reasonably achievable. In this work, we design a novel DECT imaging scheme with dual quarter scans and propose an efficient method to reconstruct the desired DECT images from the dual limited-angle projection data. We first study the characteristics of limited-angle artifacts under dual quarter scans scheme, and find that the negative and positive artifacts of DECT images are complementarily distributed in image domain because the corresponding X-rays of high- and low-energy scans are symmetric. Inspired by this finding, a fusion CT image is generated by integrating the limited-angle DECT images of dual quarter scans. This strategy enhances the true image information and suppresses the limited-angle artifacts, thereby restoring the image edges and inner structures. Utilizing the capability of neural network in the modeling of nonlinear problem, a novel Anchor network with single-entry double-out architecture is designed in this work to yield the desired DECT images from the generated fusion CT image. Experimental results on the simulated and real data verify the effectiveness of the proposed method. This work enables DECT on imaging configurations with half-scan and largely reduces scanning angles and radiation doses.

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基于双四分之一扫描锚网络的双能量 CT 重建方法。
与传统的单能量计算机断层扫描(CT)相比,双能量计算机断层扫描(DECT)能更好地分辨物质,但大多数 DECT 成像系统需要不同 X 射线光谱下的双全角投影数据。放宽对数据采集的要求是一项有吸引力的研究,以促进 DECT 在大范围领域的应用,并在合理范围内尽可能降低辐射剂量。在这项工作中,我们设计了一种新颖的双四分之一扫描 DECT 成像方案,并提出了一种从双限角投影数据重建所需 DECT 图像的有效方法。我们首先研究了双四分之一扫描方案下限角伪影的特征,发现由于高能扫描和低能扫描的相应 X 射线是对称的,因此 DECT 图像的负伪影和正伪影在图像域中呈互补分布。受这一发现的启发,通过整合双四分之一扫描的限角 DECT 图像生成了融合 CT 图像。这一策略增强了真实图像信息,抑制了限角伪影,从而还原了图像边缘和内部结构。利用神经网络在非线性问题建模方面的能力,本研究设计了一种具有单入双出结构的新型主播网络,以从生成的融合 CT 图像中生成所需的 DECT 图像。模拟和真实数据的实验结果验证了所提方法的有效性。这项工作可在半扫描成像配置上实现 DECT,并在很大程度上减少扫描角度和辐射剂量。
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来源期刊
CiteScore
4.90
自引率
23.30%
发文量
150
审稿时长
3 months
期刊介绍: Research areas within the scope of the journal include: Interaction of x-rays with matter: x-ray phenomena, biological effects of radiation, radiation safety and optical constants X-ray sources: x-rays from synchrotrons, x-ray lasers, plasmas, and other sources, conventional or unconventional Optical elements: grazing incidence optics, multilayer mirrors, zone plates, gratings, other diffraction optics Optical instruments: interferometers, spectrometers, microscopes, telescopes, microprobes
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