Open AccessIncreasing the Performance of the Iterative Computed Tomography Image Reconstruction Algorithms
Author(s) -
Shimaa Abdulsalam Khazal,
Mohammed H. Ali
Publication year - 2020
Publication title -
mağallaẗ al-nahrayn li-l-ʿulūm al-handasiyyaẗ
Language(s) - English
Resource type - Journals
eISSN - 2521-9162
pISSN - 2521-9154
DOI - 10.29194/njes.23020194
Subject(s) - iterative reconstruction , computer science , algebraic reconstruction technique , algorithm , imaging phantom , computer vision , iterative method , pixel , computation , artificial intelligence , iterative and incremental development , image quality , rendering (computer graphics) , tomography , image processing , image (mathematics) , optics , physics , software engineering
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.