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结合全变差最小化的双能CT重建

高洋 曾理

计算机应用研究2012,Vol.29Issue(3):1158-1161,4.
计算机应用研究2012,Vol.29Issue(3):1158-1161,4.DOI:10.3969/j.issn.1001-3695.2012.03.099

结合全变差最小化的双能CT重建

Dual energy CT reconstruction associated with total variation minimization

高洋 1曾理1

作者信息

  • 1. 重庆大学数学与统计学院,重庆401331
  • 折叠

摘要

Abstract

Dual energy X-ray computed tomography(CT) can be used for detecting the effective atomic number and electron density of materials, distinguishing materials with similar density but different atomic number. The accurate of the materials' effective atomic number and electron density are very important to the reconstruction of the dual energy CT. In accordance with the noise of the obtained effective atomic number and electron density images, total Variation ( TV ) minimization was applied in dual energy CT. Decomposition model of the attenuation coefficient was expressed by basis material decomposition model. Firstly , this paper realized the projection matching of high and low projections to get two sets of basis material projections of decomposition coefficient. Secondly, the decomposition coefficient could be obtained by the use of filtered backprojection(FBP) reconstruction algorithm, and then could get the effective atomic number and electron density images. Finally, algorithm which was based on TV minimization was used to process the above data. The experimental results show that dual energy CT can obtain the effective atomic number and electron density of materials, meanwhile, with the introduction of TV, dual energy CT reconstruction is capable of getting better quality images of materials' effective atomic number and electron density, and is more conducive to materials' detection.

关键词

双能CT/滤波反投影重建/全变差最小化/基材料分解/图像降噪/有效原子序数和电子密度

Key words

dual energy CT/ filtered backprojection reconstruction/ total variation minimization/ basis material decomposition/ image denoising/ effective atomic number and electron density

分类

信息技术与安全科学

引用本文复制引用

高洋,曾理..结合全变差最小化的双能CT重建[J].计算机应用研究,2012,29(3):1158-1161,4.

基金项目

国家自然科学基金资助项目(60972104) (60972104)

重庆市教委科研项目(KJ111502) (KJ111502)

计算机应用研究

OA北大核心CSCDCSTPCD

1001-3695

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