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

Author

Sukovic, Predrag ; Clinthorne, Neal H.

Author_Institution

Dept. of Biomed. Eng., Michigan Univ., Ann Arbor, MI, USA

Volume

19

Issue

11

fYear

2000

Firstpage

1075

Lastpage

1081

Abstract

Presents 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.

Keywords

computerised tomography; densitometry; image reconstruction; least mean squares methods; medical image processing; positron emission tomography; Gauss-Seidel algorithm; PET images; Si:H; amorphous silicon detectors; bone mineral densitometry; density domain; dual energy X-ray transmission tomography; high noise cases; low flux cases; metal streak artifacts removal; nonPoisson noise; nonnegativity constraints; objective function minimisation; opaque regions; penalized weighted least-squares image reconstruction; quantitative computed tomography methods; Amorphous silicon; Attenuation; Computed tomography; Detectors; Gaussian processes; Image reconstruction; Least squares methods; Positron emission tomography; Reconstruction algorithms; X-ray imaging; Algorithms; Artifacts; Computer Simulation; Data Interpretation, Statistical; Information Storage and Retrieval; Least-Squares Analysis; Models, Biological; Models, Statistical; Numerical Analysis, Computer-Assisted; Phantoms, Imaging; Radiation Dosage; Radiographic Image Enhancement; Radiographic Image Interpretation, Computer-Assisted; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; Tomography, X-Ray Computed;

fLanguage

English

Journal_Title

Medical Imaging, IEEE Transactions on

Publisher

ieee

ISSN

0278-0062

Type

jour

DOI

10.1109/42.896783

Filename

896783