Limits...
Reconstruction for 3D PET Based on Total Variation Constrained Direct Fourier Method.

Yu H, Chen Z, Zhang H, Wong KK, Chen Y, Liu H - PLoS ONE (2015)

Bottom Line: To solve the resulting minimization problem, we apply an efficient methods called the Bregman operator splitting algorithm with variable step size (BOSVS).Experiments based on Monte Carlo simulated data and real data are conducted as validations.The experiment results show that the proposed method produces higher accuracy than conventional direct Fourier (DF) (bias in BOSVS is 70% of ones in DF, variance of BOSVS is 80% of ones in DF).

View Article: PubMed Central - PubMed

Affiliation: Department of Optical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.

ABSTRACT
This paper presents a total variation (TV) regularized reconstruction algorithm for 3D positron emission tomography (PET). The proposed method first employs the Fourier rebinning algorithm (FORE), rebinning the 3D data into a stack of ordinary 2D data sets as sinogram data. Then, the resulted 2D sinogram are ready to be reconstructed by conventional 2D reconstruction algorithms. Given the locally piece-wise constant nature of PET images, we introduce the total variation (TV) based reconstruction schemes. More specifically, we formulate the 2D PET reconstruction problem as an optimization problem, whose objective function consists of TV norm of the reconstructed image and the data fidelity term measuring the consistency between the reconstructed image and sinogram. To solve the resulting minimization problem, we apply an efficient methods called the Bregman operator splitting algorithm with variable step size (BOSVS). Experiments based on Monte Carlo simulated data and real data are conducted as validations. The experiment results show that the proposed method produces higher accuracy than conventional direct Fourier (DF) (bias in BOSVS is 70% of ones in DF, variance of BOSVS is 80% of ones in DF).

No MeSH data available.


Reconstruction results.(A) Using brain phantom data, (B) Using zubal phantom data in different counting rates. The first row gives the results with DF, from left to right, the counting rate is 5 × 105,1 × 106,3 × 106,9 × 106. The second row gives the results with BOSVS.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4580435&req=5

pone.0138483.g008: Reconstruction results.(A) Using brain phantom data, (B) Using zubal phantom data in different counting rates. The first row gives the results with DF, from left to right, the counting rate is 5 × 105,1 × 106,3 × 106,9 × 106. The second row gives the results with BOSVS.

Mentions: We provide four Monte Carlo simulated sinogram for DF and BOSVS reconstruction in different kinds of counting rates and the results are illustrated as Fig 8. Obviously we can conclude that BOSVS results in a higher accuracy than DF. BOSVS can also have a good reconstructed result even in low counting rate.


Reconstruction for 3D PET Based on Total Variation Constrained Direct Fourier Method.

Yu H, Chen Z, Zhang H, Wong KK, Chen Y, Liu H - PLoS ONE (2015)

Reconstruction results.(A) Using brain phantom data, (B) Using zubal phantom data in different counting rates. The first row gives the results with DF, from left to right, the counting rate is 5 × 105,1 × 106,3 × 106,9 × 106. The second row gives the results with BOSVS.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4580435&req=5

pone.0138483.g008: Reconstruction results.(A) Using brain phantom data, (B) Using zubal phantom data in different counting rates. The first row gives the results with DF, from left to right, the counting rate is 5 × 105,1 × 106,3 × 106,9 × 106. The second row gives the results with BOSVS.
Mentions: We provide four Monte Carlo simulated sinogram for DF and BOSVS reconstruction in different kinds of counting rates and the results are illustrated as Fig 8. Obviously we can conclude that BOSVS results in a higher accuracy than DF. BOSVS can also have a good reconstructed result even in low counting rate.

Bottom Line: To solve the resulting minimization problem, we apply an efficient methods called the Bregman operator splitting algorithm with variable step size (BOSVS).Experiments based on Monte Carlo simulated data and real data are conducted as validations.The experiment results show that the proposed method produces higher accuracy than conventional direct Fourier (DF) (bias in BOSVS is 70% of ones in DF, variance of BOSVS is 80% of ones in DF).

View Article: PubMed Central - PubMed

Affiliation: Department of Optical Engineering, Zhejiang University, Hangzhou, Zhejiang, China.

ABSTRACT
This paper presents a total variation (TV) regularized reconstruction algorithm for 3D positron emission tomography (PET). The proposed method first employs the Fourier rebinning algorithm (FORE), rebinning the 3D data into a stack of ordinary 2D data sets as sinogram data. Then, the resulted 2D sinogram are ready to be reconstructed by conventional 2D reconstruction algorithms. Given the locally piece-wise constant nature of PET images, we introduce the total variation (TV) based reconstruction schemes. More specifically, we formulate the 2D PET reconstruction problem as an optimization problem, whose objective function consists of TV norm of the reconstructed image and the data fidelity term measuring the consistency between the reconstructed image and sinogram. To solve the resulting minimization problem, we apply an efficient methods called the Bregman operator splitting algorithm with variable step size (BOSVS). Experiments based on Monte Carlo simulated data and real data are conducted as validations. The experiment results show that the proposed method produces higher accuracy than conventional direct Fourier (DF) (bias in BOSVS is 70% of ones in DF, variance of BOSVS is 80% of ones in DF).

No MeSH data available.