Image reconstruction of cone-beam differential phase contrast CT using phase line integral retrieval

FU Jian; LI Chen

doi:10.3788/OPE.20152313.0491

您当前的位置：

首页 >

文章列表页 >

Image reconstruction of cone-beam differential phase contrast CT using phase line integral retrieval

更新时间：2020-08-13

- Image reconstruction of cone-beam differential phase contrast CT using phase line integral retrieval
- Optics and Precision Engineering Vol. 23, Issue 10z, Pages: 491-496(2015)
- 作者机构：
  
  北京航空航天大学机械工程及自动化学院北京,100083
- 作者简介：
- 基金信息：
- DOI：10.3788/OPE.20152313.0491
  CLC： TP391;TG115.281
- Received：05 April 2015，
  
  Revised：01 May 2015，
  
  Published：14 November 2015
- 稿件说明：
移动端阅览
傅健, 李晨,. 基于相位线积分恢复的锥束差分相衬CT图像重建[J]. 光学精密工程, 2015,23(10z): 491-496

FU Jian, LI Chen,. Image reconstruction of cone-beam differential phase contrast CT using phase line integral retrieval[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 491-496
傅健, 李晨,. 基于相位线积分恢复的锥束差分相衬CT图像重建[J]. 光学精密工程, 2015,23(10z): 491-496 DOI： 10.3788/OPE.20152313.0491.

FU Jian, LI Chen,. Image reconstruction of cone-beam differential phase contrast CT using phase line integral retrieval[J]. Editorial Office of Optics and Precision Engineering, 2015,23(10z): 491-496 DOI： 10.3788/OPE.20152313.0491.

摘要

针对X射线锥束差分相位衬度CT图像的重建

提出了一种基于傅里叶变换微分性质与FDK算法框架的重建技术。基于该技术

差分相衬CT可与现有吸收衬度CT共享相关的重建软、硬件平台。该技术利用提出的相位线积分滤波函数对面阵探测器在每个周向旋转采样视角下采集的二维差分相衬投影逐行滤波

获得物体相位函数的线积分锥束投影数据集。然后

将X射线吸收衬度锥束CT采用的FDK算法应用到恢复的线积分锥束投影数据集

重建物体三维相位图像。最后

基于三维Shepp-Logan模型

对提出的重建技术进行了仿真研究和性能分析。以塑料小球样品的X射线锥束差分相位衬度实验数据集实验验证了该方法的有效性

并与传统方法进行了比较。结果显示新方法归一化均方根重建误差小于0.2586;重建精度高于直接重建88%

满足X射线锥束差分相衬CT高精度图像重建要求。

Abstract

For the image reconstruction of an X-ray cone-beam differential phase contrast CT

a reconstruction technique based on the derivative property of Fourier transform and the FDK algorithm frame was proposed. By which the X-ray cone-beam differential phase contrast CT and absorption-based CT could share the reconstruction software and hardware. On the basis of the phase line integral filter function

the two dimensional differential contrast projection captured by an area array sensor at each rotation sampling view angle was filtered row by row

and the line integral cone-beam projection dataset of phase function for an object was obtained. Then three dimensional phase contrast CT images were reconstructed by applying the classical absorption-based FDK algorithm to the retrieved dataset. With the well-known three dimensional Shepp-Logan phantom

a numerical simulation was performed to validate the proposed method. Finally

the experimental reconstruction was verified by the dataset of a plastic sphere sample and compared with the current methods. Experimental results indicate that normalized root square error of the new method is less than 0.2586 and the reconstruction accuracy is improved by 88%. It satisfies the high-accuracy reconstruction requirements of X-ray cone-beam differential phase contrast CT.

关键词

Keywords

references

PFEIFFER F, WEITKAMP T, BUNK O, et al.. Phase retrieval and differential phase-contrast imaging with low-brilliance x-ray sources[J]. Nature Physics, 2006, 2:258-261.

邹晓兵,曾理. 锥束螺旋CT半覆盖扫描重建[J]. 光学精密工程, 2010, 18(2):434-442. ZOU X B, ZENG L. Half-cover scanning and reconstructing for helical cone-beam CT[J]. Opt. Precision Eng., 2010, 18(2):434-442.(in Chinese)

张峰,江桦,闫镔,等. 锥束CT圆轨迹半覆盖扫描的几何校正[J]. 光学精密工程, 2013, 21(7):1659-1665. ZHANG F, JIANG H, YAN B, et al.. Geometric calibration for half-cover scanning in circular cone-beam CT[J]. Opt. Precision Eng., 2013, 21(7):1659-1665.(in Chinese)

周凌宏,李翰威,徐圆,等. 锥束CT圆轨道扫描的几何校正[J]. 光学精密工程, 2014, 22(10):2847-2854. ZHOU L H, LI H W, XU Y, et al.. Geometry calibration for circular trajectory scanning in cone-beam CT[J]. Opt. Precision Eng., 2014, 22(10):2847-2854.(in Chinese)

PFEIFFER F, KOTTLER C, BUNK O, et al.. Hard x-ray phase tomography with low brilliance sources[J]. Physical Review Letters, 2007, 98:108105.

JERJEN I, REVOl V, KOTTLER C, et al.. Phase contrast cone beam tomography with an x-ray grating interferometer[J]. AIP Conference Proceedings, 2010, 1236:227-231.

FU J, LI P, WANG Q L, et al.. A reconstruction method for equidistant fan beam differential phase contrast computed tomography[J]. Physics in Medicine and Biology, 2011, 56:4529-4538.

FU J, VELROYEN A,TAN R B, et al.. A reconstruction method for cone-beam differential x-ray phase-contrast computed tomography[J]. Optics Express, 2012, 20(9):21512-21519.

KöHLER T, BRENDEL B, ROESSL E, et al.. Iterative reconstruction for differential phase contrast imaging using spherically symmetric basis functions[J]. Medical Physics, 2011, 38:4542-4545.

FU J, SCHLEEDE S, TAN R B, et al.. An algebraic iterative reconstruction technique for differential x-ray phase-contrast computed tomography[J]. Zeitschrift für Medizinische Physik,2014, 23(3):186-93.

FU J, HU X H, VELROYEN A, et al.. 3D algebraic iterative reconstruction for cone-beam X-ray differential phase-contrast computed tomography[J]. Plos one, 2015, 10(3):e0117502.

FU J, HU X H, LI C. X-ray differential phase-contrast tomographic reconstruction with a phase line integral retrieval filter[J]. Nuclear Instruments and Methods in Physics Research A, 2015, 778:14-19.

FELDKAMP L A, DAVIS L C, KRESS J W. Practical cone-beam algorithm[J]. Journal of the Optical Society of America, 1984, 1(6):612-619.

SHEPP L A. Computerized tomography and nuclear magnetic resonance[J]. Journal of Computer Assisted Tomography, 1980, 4:94-107.

庄天戈. CT原理与算法[M]. 上海:上海交通大学出版社, 1992. ZHUANG T G. CT Principle and Algorithms[M]. Shanghai:Shanghai Jiaotong University Press, 1992.(in Chinese)

Views

186

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Image reconstruction based on deep compressive sensing combined with global and local features

Lens-less imaging via score-based generative model

Hyperspectral reconstruction from RGB images based on Res2-Unet deep learning network

Skull identification based on least square canonical correlation analysis

CBCT image reconstruction using a mixed Poisson-Gaussian maximum likelihood function

Related Author

WANG Shanshan

ZHOU Yujie

XU Qianfeng

ZHONG Yuanhong

Yuhao WANG

Wenbo WAN

Qiegen LIU

Hong PENG

Related Institution

Institute of Physical Science and Information Technology， Anhui University

School of Microelectronics and Communication Engineering， Chongqing University

School of Information Engineering， Nanchang University

School of Aerospace Science and Technology， Xidian University

School of Information Engineering， Chang'an University

AI问答

Address：No.3888 Dong Nanhu Road, Changchun, Jilin, China Postal code：130033
Tel：0431-86176855 Email：gxjmgc@ciomp.ac.cn
Technical support is provided by Beijing Founder electronics co., LTD 吉ICP备11002662号-17 京公网安备11010802024621
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰