Abstract
Fast and accurate image reconstruction is the ultimate goal of iterative methods for limited-angle, few-view, interior problems, etc. Recently, a finite-detector-based projection model was proposed for iterative CT reconstructions, which was called area integral model (AIM) and has shown a high spatial resolution but with a high computational complexity. On the other hand, the distance-driven model (DDM) is the state-of-the-art technology to model forward projection and backprojection, which has shown a low computational complexity but relative low spatial resolution than AIM-based method. Inspired by the DDM, here we propose an improved distance-driven model (IDDM), which has a similar computational complexity with the DDM-based method and comparative spatial resolution with the AIM-based method. In an ordered-subset simultaneous algebraic reconstruction technique (OS-SART) framework, the AIM, IDDM and DDM are implemented and evaluated using a sinogram from a phantom experiment on a Discovery CT750 HD scanner. The results show that the computational cost of DDM- and IDDM-based methods is similar, which is 6 to 13~times faster than the AIM-based method assuming the same number of iterations. The spatial resolution of AIM- and IDDM-based method is comparable, which is better than DDM-based method in terms of full-width-of-half-maximum (FWHM).