Hybrid algorithm for few-views computed tomography of strongly absorbing media: algebraic reconstruction, TV-regularization, and adaptive segmentation

2018 ◽  
Vol 27 (04) ◽  
pp. 1 ◽  
Author(s):  
Vitaly V. Vlasov ◽  
Alexander B. Konovalov ◽  
Sergey V. Kolchugin
Keyword(s):  
Computed Tomography ◽  
Hybrid Algorithm ◽  
Adaptive Segmentation ◽  
Tv Regularization ◽  
Absorbing Media ◽  
Algebraic Reconstruction

scholarly journals Joint image reconstruction and segmentation: Comparison of two algorithms for few-view tomography

2019 ◽  
Vol 43 (6) ◽  
pp. 1008-1020 ◽  
Author(s):  
V.V. Vlasov ◽  
A.B. Konovalov ◽  
S.V. Kolchugin
Keyword(s):  
Image Reconstruction ◽  
High Frequency ◽  
Reconstruction Technique ◽  
Adaptive Segmentation ◽  
Reconstruction Accuracy ◽  
Piecewise Constant ◽  
X Ray ◽  
Exact Reconstruction ◽  
Tv Regularization ◽  
Good Potential

Two algorithms of few-view tomography are compared, specifically, the iterative Potts minimization algorithm (IPMA) and the algebraic reconstruction technique with TV-regularization and adaptive segmentation (ART-TVS). Both aim to reconstruct piecewise-constant structures, use the compressed sensing theory, and combine image reconstruction and segmentation procedures. Using a numerical experiment, it is shown that either algorithm can exactly reconstruct the Shepp-Logan phantom from as small as 7 views with noise characteristic of the medical applications of X-ray tomography. However, if an object has a complicated high-frequency structure (QR-code), the minimal number of views required for its exact reconstruction increases to 17–21 for ART-TVS and to 32–34 for IPMA. The ART-TVS algorithm developed by the authors is shown to outperform IPMA in reconstruction accuracy and speed and in resistance to abnormally high noise as well. ART-TVS holds good potential for further improvement.

Using algebraic reconstruction in computed tomography

2012 ◽  
Author(s):  
Nate D. Tang ◽  
Niels de Ruiter ◽  
J. L. Mohr ◽  
A. P. H. Butler ◽  
P. H. Butler ◽  
...  
Keyword(s):  
Computed Tomography ◽  
Algebraic Reconstruction
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