Investigation of Exact Truncated Data Image Reconstruction Algorithm on Parallel PI-Line Segments in Fan-Beam Scans

Some novel reconstruction algorithms have recently been proposed to solve the problem of reconstruction from transverse truncated projections of fan-beam scans. This paper introduced and reformulated the exact backprojection-filtration （BPF）-type reconstruction algorithm for fan-beam scans based on Zou and Pan＇s work. Subsequently, a legible and implementary BPF algorithm for region-of-interest （ROI） reconstruction is presented using projection data truncated not only in angle-scanning but also in the transverse direction. The algorithm can be widely used for fan-beam full-scans, short-scans, or super-short-scans The algorithm uses less projection data than the preceding super-short-scan. The algorithm is implemented using the Shepp-Logan phantom and some primary results are presented. Some new discoveries and implications of ROI reconstruction from truncated data are discussed, which suggests that the BPF algorithm can be used in the ROI reconstruction from truncated projections.

Region of Interest Imaging for a General Trajectory with the Rebinned BPF Algorithm

The back-projection-filtration （BPF） algorithm has been applied to image reconstruction for cone-beam configurations with general source trajectories. The BPF algorithm can reconstruct 3-D region- of-interest （ROI） images from data containing truncations. However, like many other existing algorithms for cone-beam configurations, the BPF algorithm involves a back-projection with a spatially varying weighting factor, which can result in the non-uniform noise levels in reconstructed images and increased computation time. In this work, we propose a BPF algorithm to eliminate the spatially varying weighting factor by using a rebinned geometry for a general scanning trajectory. This proposed BPF algorithm has an improved noise property, while retaining the advantages of the original BPF algorithm such as minimum data requirement.