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

arXiv: https://arxiv.org/abs/2305.19767 · HTML: https://mlsanity.com/paper/2305.19767/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 46 references that are in the map.
- First posted on arXiv 31 May 2023.

## Builds on (most cited first, 2 of 2)

- [MetaInv-Net: Meta Inversion Network for Sparse View CT Image Reconstruction](https://mlsanity.com/paper/2006.00171/) (2020)
- [BPF Algorithms for Multiple Source-Translation Computed Tomography Reconstruction](https://mlsanity.com/paper/2305.18878/) (2023)

## Built on by (most cited first, 2 of 2)

- [OSNet & MNetO: Two Types of General Reconstruction Architectures for Linear Computed Tomography in Multi-Scenarios](https://mlsanity.com/paper/2309.11858/) (2023)
- [Geometric Artifact Correction for Symmetric Multi-Linear Trajectory CT: Theory, Method, and Generalization](https://mlsanity.com/paper/2408.15069/) (2024)

## Abstract (arXiv)

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.