View-driven compressed sensing method of CT image reconstruction

Abstract

In order to significantly reducing the X-ray dose of CT examination, this study focuses on reconstructing the tomographic images from sparse projection data with sufficient accuracy. Aiming at two-dimensional (2D) image reconstruction of fan-beam projection under circular scanning, this paper proposes the view-driven system model and designs a CT iterative image reconstruction method by combining the iterative algorithm and the compressed sensing theory. The simulation results show that the algorithm has high numerical accuracy, low computational complexity, less memory overhead, and strong engineering practicability under the condition of ultra-sparse projection data (no more than 20 view angles for fan-beam scanning in the range of [0,2π)).