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.

scholarly journals Variable Weighted Ordered Subset Image Reconstruction Algorithm

2006 ◽  
Vol 2006 ◽  
pp. 1-7 ◽  
Author(s):  
Jinxiao Pan ◽  
Tie Zhou ◽  
Yan Han ◽  
Ming Jiang
Keyword(s):  
Numerical Simulation ◽  
Iterative Reconstruction ◽  
Reconstruction Algorithm ◽  
Reconstruction Technique ◽  
Algebraic Reconstruction Technique ◽  
Reconstruction Algorithms ◽  
Ct Data ◽  
Simultaneous Algebraic Reconstruction Technique ◽  
Algebraic Reconstruction

We propose two variable weighted iterative reconstruction algorithms (VW-ART and VW-OS-SART) to improve the algebraic reconstruction technique (ART) and simultaneous algebraic reconstruction technique (SART) and establish their convergence. In the two algorithms, the weighting varies with the geometrical direction of the ray. Experimental results with both numerical simulation and real CT data demonstrate that the VW-ART has a significant improvement in the quality of reconstructed images over ART and OS-SART. Moreover, both VW-ART and VW-OS-SART are more promising in convergence speed than the ART and SART, respectively.

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 Increasing the Performance of the Iterative Computed Tomography Image Reconstruction Algorithms

2020 ◽  
Vol 23 (2) ◽  
pp. 194-203
Author(s):  
Shimaa Abdulsalam Khazal ◽  
Mohammed Hussein Ali
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Iterative Algorithms ◽  
Computation Time ◽  
Ct Imaging ◽  
Reconstruction Technique ◽  
Reconstruction Algorithms ◽  
Reconstruction Process ◽  
Simulation Results ◽  
Reconstruction Time

Computed tomography (CT) imaging is an important diagnostic tool. CT imaging facilitates the internal rendering of a scanned object by measuring the attenuation of beams of X-ray radiation. CT employs a mathematical technique of image reconstruction; those techniques are classified as; analytical and iterative. The iterative reconstruction (IR) 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. In this paper the reconstruction time of an IR algorithm is minimized through the employment of an adaptive region growing segmentation method that focuses the image reconstruction process on a specified region, thus ignoring unwanted pixels that increase the computation time. This method is tested on the iterative algebraic reconstruction technique (ART) algorithm. Some phantom images are used in this paper to demonstrate the effects of the segmentation process. The simulation results are executed using MATLAB (version R2018b) programming language, and a computer system with the following specifications: CPU core i7 (2.40 GHz) for processing. Simulation results indicate that this method will reduce the reconstruction time of the iterative algorithms, and will enhance the quality of the reconstructed image.

scholarly journals Evaluation of image reconstruction algorithms in cone-beam computed tomography technique

2021 ◽  
Vol 9 (4) ◽  
pp. 41-47
Author(s):  
Thuy Duong Tran ◽  
Ngoc Ha Bui
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Cone Beam ◽  
Materials Testing ◽  
Projection Data ◽  
Reconstruction Technique ◽  
Reconstruction Algorithms ◽  
Medical Diagnostic ◽  
Iterative Reconstruction Technique ◽  
Image Reconstruction Algorithms

Cone-beam computed tomography (CBCT) technique is largely used in medical diagnostic imaging and nondestructive materials testing, especially in cases which require fast times and high accuracy level. In this paper, the pros and cons of Feldkamp-Davis-Kress (FDK) and simultaneous iterative reconstruction technique (SIRT) algorithms used in CBCT technique is studied. The method of simulating CBCT systems is also used to provide richer projection data, which helps the research to evaluate many aspects of algorithms.

scholarly journals Suppression of Cone-Beam Artefacts with Direct Iterative Reconstruction Computed Tomography Trajectories (DIRECTT)

2021 ◽  
Vol 7 (8) ◽  
pp. 147
Author(s):  
Sotirios Magkos ◽  
Andreas Kupsch ◽  
Giovanni Bruno
Keyword(s):  
Computed Tomography ◽  
Cone Beam Computed Tomography ◽  
Iterative Reconstruction ◽  
Cone Beam ◽  
Back Projection ◽  
Projection Algorithms ◽  
Filtered Back Projection ◽  
Tomography Data

The reconstruction of cone-beam computed tomography data using filtered back-projection algorithms unavoidably results in severe artefacts. We describe how the Direct Iterative Reconstruction of Computed Tomography Trajectories (DIRECTT) algorithm can be combined with a model of the artefacts for the reconstruction of such data. The implementation of DIRECTT results in reconstructed volumes of superior quality compared to the conventional algorithms.

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