Abstract
Computed tomography (CT) is a widely used imaging technique in medical diagnosis. Among the latest advances in CT imaging techniques, the use of cone-beam X-ray projections, instead of the usual planar fan beam, promises faster yet safer 3D imaging in comparison to the previous CT imaging methodologies. This technique is called Cone Beam CT (CBCT). However, these advantages come at the expense of a more challenging 3D reconstruction problem that is still an active research area to improve the speed and quality of image reconstruction. In this paper, we propose a rapid parallel Multiplicative Algebraic Reconstruction Technique (rpMART) via a vectorization process for CBCT which gives more accurate and faster reconstruction even with a lower number of projections via parallel computing. We have compared rpMART with the parallel version of Algebraic Reconstruction Technique (pART) and the conventional non-parallel versions of npART, npMART and Feldkamp, Davis, and Kress (npFDK) techniques. The results indicate that the reconstructed volume images from rpMART provide a higher image quality index of 0.99 than the indices of pART and npFDK of 0.80 and 0.39, respectively. Also the proposed implementation of rpMART and pART via parallel computing significantly reduce the reconstruction time from more than 6h with npART and npMART to 580 and 560s with the full 360° projections data, respectively. We consider that rpMART could be a better image reconstruction technique for CBCT in clinical applications instead of the widely used FDK method.