ACCELERATED ITERATIVE RECONSTRUCTION OF PHANTOM «ROZI» BY OS-SART METHOD USING ORDERED SUBSET PROJECTIONS

Abstract

The statistical maximum likelihood (EM) method and the algebraic reconstruction method with simultaneous iterations (SART) are two methods of iterative tomographic reconstruction. These algorithms are often used when the projection data contains a large amount of statistical noise or has been obtained from a limited range of angles. One of the popular approaches used to increase the rate of convergence of these algorithms is to perform a correction of the current approximation of the reconstructed object on subsets of the projection data. The desire to increase the convergence rate of the iterative methods led to the use of ordered subsets of projections for both the maximum likelihood method of EM (OS-EM) and for the algebraic reconstruction method with simultaneous iterations of SART (OS-SART). The efficiency of using ordered subsets of projections was first established for sequential programs that run on the central processor of the computer (CPU). In this work, both these methods have been accelerated by using the OpenGL graphics library by mirroring them on the graphics processor architecture of the video card.

Keywords

• ordered-subsets
• cone-beam tomography
• iterative reconstruction
• regularization