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.

Algebraic Reconstruction Technique in Image Reconstruction Based on Data Mining

2008 ◽  
pp. 3493-3508
Author(s):  
Zhong Qu
Keyword(s):  
Computed Tomography ◽  
Data Mining ◽  
Image Reconstruction ◽  
Iteration Process ◽  
Algebraic Method ◽  
Projection Data ◽  
Reconstruction Technique ◽  
Algebraic Reconstruction Technique ◽  
Industrial Computed Tomography ◽  
Algebraic Reconstruction

Image reconstruction is one of the key technologies in industrial computed tomography. In this paper, an efficient iterative image reconstruction algorithm in industrial computed tomography with the narrow fan-beam projection based on data mining was discussed in detail. In image reconstruction, algebraic technique has un-replaceable advantage when data is incomplete or noise is high. However algebraic method has been highly limited in applications for its low reconstruction speed. In order to resolve this problem, the algebraic reconstruction technique (ART) as a new iterative method, is introduced to accelerate the iteration process and increase the reconstruction speed. Experiment results clearly demonstrate that the algorithm reconstruction technique can effectively improve the quality of images reconstruction in dealing with incomplete projection or noisy projection data.

scholarly journals An Accelerated Iterative Cone Beam Computed Tomography Image Reconstruction Approach

2019 ◽  
Vol 22 (4) ◽  
pp. 307-314
Author(s):  
Shimaa Abdulsalam Khazal ◽  
Mohammed Hussein Ali
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Iterative Reconstruction ◽  
Cone Beam ◽  
Reconstruction Technique ◽  
Algebraic Reconstruction Technique ◽  
Reconstruction Algorithms ◽  
Reconstruction Process ◽  
Reconstruction Time ◽  
Algebraic Reconstruction

Cone-beam computed tomography (CBCT) is an indispensable method that reconstructs three dimensional (3D) images. CBCT employs a mathematical technique of reconstruction, which reveals the anatomy of the patient’s body through the measurements of projections. The mathematical techniques employed in the reconstruction process are classified as; analytical, and iterative. The iterative reconstruction methods have been proven to be superior over the analytical methods, but due to their prolonged reconstruction time those methods are excluded from routine use in clinical applications. The aim of this research is to accelerate the iterative methods by performing the reconstruction process using a graphical processing unit (GPU). This method is tested on two iterative-reconstruction algorithms (IR), the algebraic reconstruction technique (ART), and the multiplicative algebraic reconstruction technique (MART). The results are compared against the traditional ART, and MART. A 3D test head phantom image is used in this research to demonstrate results of the proposed method on the reconstruction algorithms. The simulation results are executed using MATLAB (version R2018b) programming language and computer system with the following specifications: CPU core i7 (2.40 GHz) for the processing, with a NIVDIA GEFORCE GPU. Experimental results indicate, that this method reduces the reconstruction time for the iterative algorithms.

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