Analytical reconstructions of full-scan multiple source-translation computed tomography under large field of views

TL;DR

This paper develops and evaluates analytical backprojection filtration algorithms for high-quality, large field-of-view multiple source-translation CT, addressing errors in previous methods and proposing improvements for extended FOV imaging.

Contribution

It introduces a redundancy-weighted function for full-scan mSTCT and demonstrates improved reconstruction quality over existing algorithms in extended FOV scenarios.

Findings

FS-BPF achieves high-quality, stable images with large FOVs.

FS-BPF requires more projections than FD-BPF for optimal results.

Recommendations are provided for algorithm selection based on practical FOV extension needs.

Abstract

This paper is to investigate the high-quality analytical reconstructions of multiple source-translation computed tomography (mSTCT) under an extended field of view (FOV). Under the larger FOVs, the previously proposed backprojection filtration (BPF) algorithms for mSTCT, including D-BPF and S-BPF (their differences are different derivate directions along the detector and source, respectively), make some errors and artifacts in the reconstructed images due to a backprojection weighting factor and the half-scan mode, which deviates from the intention of mSTCT imaging. In this paper, to achieve reconstruction with as little error as possible under the extremely extended FOV, we combine the full-scan mSTCT (F-mSTCT) geometry with the previous BPF algorithms to study the performance and derive a suitable redundancy-weighted function for F-mSTCT. The experimental results indicate FS-BPF can get high-quality, stable images under the extremely extended FOV of imaging a large object, though it requires more projections than FD-BPF. Finally, for different practical requirements in extending FOV imaging, we give suggestions on algorithm selection.