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

作者：Junru Ren, Wenkun Zhang, Yizhong Wang, Ningning Liang, Linyuan Wang, Ailong Cai, Shaoyu Wang, Zhizhong Zheng, Lei Li, Bin Yan · 发表于：Journal of X-Ray Science and Technology · 年份：2024 · DOI：10.3233/xst-230245 · 被引用次数：2 · 研究领域：Advanced X-ray and CT Imaging、Medical Imaging Techniques and Applications、Radiation Dose and Imaging

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 propo...