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Abstract
An improvement to a current methodology for testing iterative reconstruction algorithms is presented. This modification consists of the use of a multidimensional global optimization algorithm for the best estimate of the free parameters of the reconstruction process. This algorithm is based on a probabilistic random search method. This tool allows the best performance of the reconstruction algorithms to be to obtained without any prejudice in the parameter selection. This methodology has been applied to testing an algebraic reconstruction technique (ART) algorithm performance using classical cubic-shaped voxels and spherical symmetric basis functions, also known as blobs, as the basis functions for image representation in three-dimensional X-ray cone-beam transmission tomography.