Penalized weighted least-squares image reconstruction for dual energy X-ray transmission tomography

被引：158

作者：

Sukovic, P ^{[1
]}

Clinthorne, NH

机构：

[1] Univ Michigan, Dept Biomed Engn, Ann Arbor, MI 48109 USA

[2] Univ Michigan, Dept Internal Med, Div Nucl Med, Ann Arbor, MI 48109 USA

来源：

IEEE TRANSACTIONS ON MEDICAL IMAGING | 2000年 / 19卷 / 11期

关键词：

dual energy X-ray transmission tomography; statistical image reconstruction;

D O I：

10.1109/42.896783

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We present a dual-energy (DE) transmission computed tomography (CT) reconstruction method. It is statistically motivated and features nonnegativity constraints in the density domain. A penalized weighted least squares (PWLS) objective function has been chosen to handle the non-Poisson noise added by amorphous silicon (aSi:H) detectors. A Gauss-Seidel algorithm has been used to minimize the objective function. The behavior of the method in terms of bias/standard deviation tradeoff has been compared to that of a DE method that is based on filtered back projection (FBP). The advantages of the DE PWLS method are largest for high noise and/or low flux cases, Qualitative results suggest this as well. Also, the reconstructed images of an object with opaque regions are presented. Possible applications of the method are: attenuation correction for positron emission tomography (PET) images, various quantitative computed tomography (QCT) methods such as bone mineral densitometry (BMD), and the removal of metal streak artifacts.

引用

页码：1075 / 1081

页数：7

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