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Go to Editorial ManagerComputed 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.
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.