Iterative CT Reconstruction using Continuous Model

摘要

A typical iterative CT reconstruction using SART involves ray-driven forward projection and voxel-driven backward projection. Bilinear interpolation is usually applied on image data for forward projection, and linear interpolation is usually applied on projection data for backward projection, when both data are represented using discrete samples in 2D fan-beam geometry. The applied interpolations, however, may affect the spatial resolution, bias and noise properties of the reconstruction. A basis function (such as blob and spline) is therefore applied to formulate a continuous model for the image data to reduce bias. In this paper we propose to apply the blob representation on the projection data and explore its effectiveness. In this way we use continuous model for the data of projection difference during backward projection, and we avoid the linear interpolation in this process. Experimental results show that the proposed scheme is able to provide higher spatial resolution than linear interpolation, while introducing more local variations in the reconstruction. However, the introduced local variations may be reduced with the combination of total variation (TV) minimization. The proposed scheme is therefore able to provide improved spatial resolution while keeping low local variations in reconstructions.