Multilevel algebraic reconstruction technique for x-ray computed tomography

1997 ◽  
Vol 24 (3) ◽  
pp. 473-473 ◽  
Author(s):  
Huaiqun Guan
Keyword(s):  
Computed Tomography ◽  
Reconstruction Technique ◽  
Algebraic Reconstruction Technique ◽  
X Ray ◽  
X Ray Computed ◽  
Algebraic Reconstruction

scholarly journals Level-set reconstruction algorithm for ultrafast limited-angle X-ray computed tomography of two-phase flows

2015 ◽  
Vol 373 (2043) ◽  
pp. 20140395 ◽  
Author(s):  
M. Bieberle ◽  
U. Hampel
Keyword(s):  
Computed Tomography ◽  
Level Set ◽  
Reconstruction Algorithm ◽  
Projection Data ◽  
Reconstruction Technique ◽  
Two Phase Flows ◽  
Two Phase ◽  
X Ray ◽  
X Ray Computed ◽  
Limited Angle

Tomographic image reconstruction is based on recovering an object distribution from its projections, which have been acquired from all angular views around the object. If the angular range is limited to less than 180° of parallel projections, typical reconstruction artefacts arise when using standard algorithms. To compensate for this, specialized algorithms using a priori information about the object need to be applied. The application behind this work is ultrafast limited-angle X-ray computed tomography of two-phase flows. Here, only a binary distribution of the two phases needs to be reconstructed, which reduces the complexity of the inverse problem. To solve it, a new reconstruction algorithm (LSR) based on the level-set method is proposed. It includes one force function term accounting for matching the projection data and one incorporating a curvature-dependent smoothing of the phase boundary. The algorithm has been validated using simulated as well as measured projections of known structures, and its performance has been compared to the algebraic reconstruction technique and a binary derivative of it. The validation as well as the application of the level-set reconstruction on a dynamic two-phase flow demonstrated its applicability and its advantages over other reconstruction algorithms.

BIFURCATION ANALYSIS OF ITERATIVE IMAGE RECONSTRUCTION METHOD FOR COMPUTED TOMOGRAPHY

2008 ◽  
Vol 18 (04) ◽  
pp. 1219-1225 ◽  
Author(s):  
TETSUYA YOSHINAGA ◽  
YOSHIHIRO IMAKURA ◽  
KEN'ICHI FUJIMOTO ◽  
TETSUSHI UETA
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Computational Method ◽  
Reconstruction Technique ◽  
Reconstruction Method ◽  
Algebraic Reconstruction Technique ◽  
Reconstruction Algorithms ◽  
Iterative Image Reconstruction ◽  
Multiplicative Algebraic Reconstruction Technique ◽  
Algebraic Reconstruction

Of the iterative image reconstruction algorithms for computed tomography (CT), the power multiplicative algebraic reconstruction technique (PMART) is known to have good properties for speeding convergence and maximizing entropy. We analyze here bifurcations of fixed and periodic points that correspond to reconstructed images observed using PMART with an image made of multiple pixels and we investigate an extended PMART, which is a dynamical class for accelerating convergence. The convergence process for the state in the neighborhood of the true reconstructed image can be reduced to the property of a fixed point observed in the dynamical system. To investigate the speed of convergence, we present a computational method of obtaining parameter sets in which the given real or absolute values of the characteristic multiplier are equal. The advantage of the extended PMART is verified by comparing it with the standard multiplicative algebraic reconstruction technique (MART) using numerical experiments.

scholarly journals poly-DART: A discrete algebraic reconstruction technique for polychromatic X-ray CT

2019 ◽  
Vol 27 (23) ◽  
pp. 33670
Author(s):  
Nathanaël Six ◽  
Jan De Beenhouwer ◽  
Jan Sijbers
Keyword(s):  
Reconstruction Technique ◽  
Algebraic Reconstruction Technique ◽  
X Ray ◽  
Algebraic Reconstruction
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