Graphics processing unit-accelerated iterative tomographic reconstruction with strip-integral system model

In tomographic reconstruction, the major factors that affect the performance of an algorithm are the computational efficiency and the reconstruction accuracy. The computational efficiency has recently been achieved by using graphics processing units (GPUs). However, efforts to improve the accuracy of modeling a projector-backprojector pair have been hindered by the need for approximations to maximize the efficiency of the GPU. The approximations used for modeling a projector-backprojector pair often cause artifacts in reconstruction which propagate through iterations and lower the accuracy of reconstruction. In addition to the approximations, the unmatched projector-backprojector pairs often used for GPU-accelerated methods also cause additional errors in iterative reconstruction. For reconstruction with relatively low resolution, the degradation due to these artifacts and errors becomes more significant as the number of iterations is increased. In this work, we develop GPU-accelerated methods for 2-D reconstruction without using any approximations for parallelizing the projection and backprojection operations. The methods of projection and backprojection we use in this work are the strip area-based method and the distance-driven method. Our proposed methods were successfully implemented on the GPU and resulted in high-performance computing in iterative reconstruction while retaining the reconstruction accuracy by providing a perfectly matched projector-backprojector pair. (C) 2012 Society of Photo-Optical Instrumentation Engineers (SPIE). [DOI: 10.1117/1.OE.51.9.093203]