A Parametric Physical Model-Based X-Ray Spectrum Estimation Approach for CT Imaging

被引:2
作者
Chang, Shaojie [1 ,2 ]
Zhang, Chaoyang [1 ]
Mou, Xuanqin [1 ]
Xu, Qiong [3 ]
He, Lijun [1 ]
Chen, Xi [1 ]
机构
[1] Xi An Jiao Tong Univ, Sch Informat & Commun Engn, Xian 710049, Shaanxi, Peoples R China
[2] Mayo Clin, Dept Radiol, Rochester, MN 55905 USA
[3] Chinese Acad Sci, Inst High Energy Phys, Beijing Engn Res Ctr Radiog Tech & Equipment, Beijing 100864, Peoples R China
关键词
Computed tomography; Image reconstruction; X-ray imaging; Spectral analysis; Attenuation; Image segmentation; Phantoms; CT imaging; spectrum estimation; X-ray spectrum model;
D O I
10.1109/TRPMS.2024.3374702
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
X-ray spectrum plays an essential role in CT applications. Since it is difficult to measure X-ray spectrum directly in practice, X-ray spectrum is always indirectly obtained by using transmission measurements through a calibration phantom of known thickness and materials. These methods are independent of CT image reconstruction and bring extra cost. To solve this problem, we propose a parametric physical model-based X-ray spectrum estimation algorithm for CT imaging. First, an X-ray spectrum model with six parameters is proposed, which is derived from the X-ray imaging physics. Second, a template image containing different material components can be obtained by segmenting CT reconstructed images with a simple method. And the estimated projections can be calculated by reprojecting the template image with the proposed spectrum model. Finally, the six model parameters can be solved by iteratively minimizing the error between the estimated projection and real measurements. The effectiveness of the proposed method has been validated on both simulated and real data. Experimental results demonstrate that the proposed method can estimate the accurate spectra at different energies and provide a good reconstruction of characteristic radiations without extra cost.
引用
收藏
页码:532 / 539
页数:8
相关论文
共 28 条
[1]   Simplified Statistical Image Reconstruction for X-ray CT With Beam-Hardening Artifact Compensation [J].
Abella, Monica ;
Martinez, Cristobal ;
Desco, Manuel ;
Jose Vaquero, Juan ;
Fessler, Jeffrey A. .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2020, 39 (01) :111-118
[2]   DETERMINATION OF DIAGNOSTIC-X-RAY SPECTRA WITH CHARACTERISTIC RADIATION USING ATTENUATION ANALYSIS [J].
ARCHER, BR ;
WAGNER, LK .
MEDICAL PHYSICS, 1988, 15 (04) :637-641
[3]  
Back T., 1997, HDB EVOLUTIONARY COM
[4]  
Bertin EP., 1978, INTRO XRAY SPECTROME
[5]   A full-spectral Bayesian reconstruction approach based on the material decomposition model applied in dual-energy computed tomography [J].
Cai, C. ;
Rodet, T. ;
Legoupil, S. ;
Mohammad-Djafari, A. .
MEDICAL PHYSICS, 2013, 40 (11)
[6]  
Chang S., 2016, IEEE NUCL SCI S MED, P1
[7]   Parameter-free Bayesian Reconstruction for Dual Energy Computed Tomography [J].
Chang, Shaojie ;
Gao, Yongfeng ;
Lu, Siming ;
Van, Hao ;
Liang, Zhengrong .
MEDICAL IMAGING 2021: PHYSICS OF MEDICAL IMAGING, 2021, 11595
[8]   Spectrum Estimation based on a Parametric Physical Model for CT [J].
Chang, Shaojie ;
Chen, Xi ;
Li, Yang ;
Mou, Xuanqin .
MEDICAL IMAGING 2020: PHYSICS OF MEDICAL IMAGING, 2020, 11312
[9]   Spectrum Estimation-Guided Iterative Reconstruction Algorithm for Dual Energy CT [J].
Chang, Shaojie ;
Li, Mengfei ;
Yu, Hengyong ;
Chen, Xi ;
Deng, Shiwo ;
Zhang, Peng ;
Mou, Xuanqin .
IEEE TRANSACTIONS ON MEDICAL IMAGING, 2020, 39 (01) :246-258
[10]  
Chang X., inProc. Develop