Abstract
This work considers synergistic multi-spectral CT reconstruction where information from all available energy channels is combined to improve the reconstruction of each individual channel. We propose to fuse these available data (represented by a single sinogram) to obtain a polyenergetic image which keeps structural information shared by the energy channels with increased signal-to-noise ratio. This new image is used as prior information during a channel-by-channel minimization process through the directional total variation. We analyse the use of directional total variation within variational regularization and iterative regularization. Our numerical results on simulated and experimental data show improvements in terms of image quality and in computational speed. This article is part of the theme issue 'Synergistic tomographic image reconstruction: part 2'.
| Original language | English |
|---|---|
| Article number | 20200198 |
| Journal | Philosophical transactions. Series A, Mathematical, physical, and engineering sciences |
| Volume | 379 |
| Issue number | 2204 |
| Early online date | 5 Jul 2021 |
| DOIs | |
| Publication status | Published - 23 Aug 2021 |
Bibliographical note
20 pages, 16 figuresFunding
Data accessibility. The data and code are available on http://doi.org/10.5281/zenodo.4765104. Authors’ contributions. E.C. carried out the numerical computations and drafted the manuscript. M.J.E. designed the project, advised E.C. and supported writing the manuscript. S.S. and A.M. acquired and processed real and synthetic data. All authors read and approved the manuscript. Competing interests. We declare we have no competing interests. Funding. M.J.E. acknowledges support from the EPSRC (EP/S026045/1, EP/T026693/1), the Faraday Institution (EP/T007745/1) and the Leverhulme Trust (ECF-2019-478). E.C. acknowledges support from the CMM ANID PIA AFB170001 and Beca Doctorado Nacional Conicyt.
Keywords
- math.OC
- cs.NA
- eess.IV
- math.NA
- 65K10 (Primarly) 94A08, 68U10 (Secondary)