journal article·2013-10

A Graphical Processing Unit–Based Parallel Implementation of Multiplicative Algebraic Reconstruction Technique Algorithm for Limited View Tomography

Manish Bajpai, Phalguni Gupta, Prabhat Munshi, V. Titarenko, P. J. Withers

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Abstract

This article proposes an efficient two-dimensional (2D) pixel-driven multiplicative algebraic reconstruction technique (PdMART) on a general purpose graphical processing unit (GPU), Nvidia graphics card GTX-275. It has been tested on numerical data and also on real data that have been obtained from the micro–computed tomography scanner installed at University of Manchester. We have used real data having 90 projections and 256 rays in each projection to test the algorithm. The real data has been obtained by scanning the graphite core object of size 30 mm × 30 mm. It has been found that GPU can help PdMART to generate the weight matrix for the 256 × 256 pixel grid within a second which is very fast compared to any sequential machine. Experimental results reveal that PdMART on GPU is computationally inexpensive. Preliminary results also indicate much better performance (as compared to popular Fourier methods) for cases of limited-view projection data as is the case for the upcoming laminographic tomography machines.
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Research context

OpenAlex topics: Medical Imaging Techniques and Applications · Advanced MRI Techniques and Applications · Advanced X-ray and CT Imaging

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