scholarly journals NUFFT-Based Iterative Image Reconstruction via Alternating Direction Total Variation Minimization for Sparse-View CT

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Bin Yan ◽  
Zhao Jin ◽  
Hanming Zhang ◽  
Lei Li ◽  
Ailong Cai
Keyword(s):  
Image Reconstruction ◽  
Total Variation ◽  
Imaging System ◽  
Reconstruction Technique ◽  
Ct Reconstruction ◽  
Time Duration ◽  
Total Variation Minimization ◽  
Scanning Method ◽  
X Ray ◽  
Alternating Direction

Sparse-view imaging is a promising scanning method which can reduce the radiation dose in X-ray computed tomography (CT). Reconstruction algorithm for sparse-view imaging system is of significant importance. The adoption of the spatial iterative algorithm for CT image reconstruction has a low operation efficiency and high computation requirement. A novel Fourier-based iterative reconstruction technique that utilizes nonuniform fast Fourier transform is presented in this study along with the advanced total variation (TV) regularization for sparse-view CT. Combined with the alternating direction method, the proposed approach shows excellent efficiency and rapid convergence property. Numerical simulations and real data experiments are performed on a parallel beam CT. Experimental results validate that the proposed method has higher computational efficiency and better reconstruction quality than the conventional algorithms, such as simultaneous algebraic reconstruction technique using TV method and the alternating direction total variation minimization approach, with the same time duration. The proposed method appears to have extensive applications in X-ray CT imaging.

scholarly journals Distributed Reconstruction via Alternating Direction Method

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Linyuan Wang ◽  
Ailong Cai ◽  
Hanming Zhang ◽  
Bin Yan ◽  
Lei Li ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Total Variation ◽  
Reconstruction Algorithm ◽  
Alternating Direction Method ◽  
Ct Image ◽  
Total Variation Minimization ◽  
Considerable Research ◽  
Alternating Direction ◽  
Ct Image Reconstruction

With the development of compressive sensing theory, image reconstruction from few-view projections has received considerable research attentions in the field of computed tomography (CT). Total-variation- (TV-) based CT image reconstruction has been shown to be experimentally capable of producing accurate reconstructions from sparse-view data. In this study, a distributed reconstruction algorithm based on TV minimization has been developed. This algorithm is very simple as it uses the alternating direction method. The proposed method can accelerate the alternating direction total variation minimization (ADTVM) algorithm without losing accuracy.

Inexact Distributed Reconstruction via Alternating Direction Method

2014 ◽  
Vol 511-512 ◽  
pp. 417-420
Author(s):  
Lin Yuan Wang ◽  
Ai Long Cai ◽  
Bin Yan ◽  
Lei Li ◽  
Han Ming Zhang ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Total Variation ◽  
Reconstruction Algorithm ◽  
Alternating Direction Method ◽  
Experimental Results ◽  
Ct Image ◽  
Total Variation Minimization ◽  
Alternating Direction ◽  
Proximal Points ◽  
Ct Image Reconstruction

Total variation (TV)-based CT image reconstruction has been shown to be experimentally capable of producing accurate reconstructions from sparse-view data. In this study, an inexact distributed reconstruction algorithm based on TV minimization has been developed. The algorithm is relatively simple as it uses the inexact alternating direction method, which involves linearization and proximal points techniques. The outstanding acceleration factor is achieved as the algorithm distributes the data and computation to individual nodes. Experimental results demonstrate that the proposed method can accelerate the alternating direction total variation minimization (ADTVM) algorithm with very little accuracy loss.

Evaluation of reconstruction algorithms for a stationary digital breast tomosynthesis system using a carbon nanotube X-ray source array

2020 ◽  
Vol 28 (6) ◽  
pp. 1157-1169
Author(s):  
Zhanli Hu ◽  
Zixiang Chen ◽  
Chao Zhou ◽  
Xuda Hong ◽  
Jianwei Chen ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Imaging System ◽  
Digital Breast Tomosynthesis ◽  
Reconstruction Technique ◽  
Reconstruction Algorithms ◽  
Breast Tomosynthesis ◽  
X Ray ◽  
Noise Ratio ◽  
Set Up ◽  
Source Array

Breast cancer is the most frequently diagnosed cancer in women worldwide. Digital breast tomosynthesis (DBT), which is based on limited-angle tomography, was developed to solve tissue overlapping problems associated with traditional breast mammography. However, due to the problems associated with tube movement during the process of data acquisition, stationary DBT (s-DBT) was developed to allow the X-ray source array to stay stationary during the DBT scanning process. In this work, we evaluate four widely used and investigated DBT image reconstruction algorithms, including the commercial Feldkamp-Davis-Kress algorithm (FBP), the simultaneous iterative reconstruction technique (SIRT), the simultaneous algebraic reconstruction technique (SART) and the total variation regularized SART (SART-TV) for an s-DBT imaging system that we set up in our own laboratory for studies using a semi-elliptical digital phantom and a rubber breast phantom to determine the most superior algorithm for s-DBT image reconstruction among the four algorithms. Several quantitative indexes for image quality assessment, including the peak signal-noise ratio (PSNR), the root mean square error (RMSE) and the structural similarity (SSIM), are used to determine the best algorithm for the imaging system that we set up. Image resolutions are measured via the calculation of the contrast-to-noise ratio (CNR) and artefact spread function (ASF). The experimental results show that the SART-TV algorithm gives reconstructed images with the highest PSNR and SSIM values and the lowest RMSE values in terms of image accuracy and similarity, along with the highest CNR values calculated for the selected features and the best ASF curves in terms of image resolution in the horizontal and vertical directions. Thus, the SART-TV algorithm is proven to be the best algorithm for use in s-DBT image reconstruction for the specific imaging task in our study.

scholarly journals Image reconstruction algorithm based on inexact alternating direction total-variation minimization

2013 ◽  
Vol 62 (19) ◽  
pp. 198701
Author(s):  
Wang Lin-Yuan ◽  
Zhang Han-Ming ◽  
Cai Ai-Long ◽  
Yan Bin ◽  
Li Lei ◽  
...  
Keyword(s):  
Image Reconstruction ◽  
Total Variation ◽  
Reconstruction Algorithm ◽  
Total Variation Minimization ◽  
Image Reconstruction Algorithm ◽  
Alternating Direction
Sign in / Sign up

Export Citation Format

Share Document