Royal Society Theme issue Synergistic tomographic image reconstruction: part 1

Compiled and edited by Charalampos Tsoumpas, Jakob Sauer Jørgensen, Christoph Kolbitsch and Kris Thielemans.

Traditionally, tomographic image reconstruction has focused on estimating images from a single modality and acquisition. This theme issue focuses on synergistic image reconstruction which aims to utilise both similarities and complementary information between different data to make the synergistic combination of data offer more than the sum of its parts.

The issue is comprised of two parts, and this first part includes investigations in multi-spectral X-ray computed tomography; multi-sequence magnetic resonance imaging and multi-modality imaging systems; and electric impedance tomography combined with quasi-static elasticity imaging.

Part 2 will publish on 05 July 2021.

This issue will soon be available to buy in print. Visit our information for readers page for more purchasing options.

Table of Contents

INTRODUCTION

Introduction
Synergistic tomographic image reconstruction: part 1.
Charalampos Tsoumpas, Jakob Sauer Jørgensen, Christoph Kolbitsch and Kris Thielemans.
Published:10 May 2021Article ID:20200189.
https://doi.org/10.1098/rsta.2020.0189.

ARTICLES

(An overview of) Synergistic reconstruction for multimodality/multichannel imaging methods.
Simon R. Arridge, Matthias J. Ehrhardt and Kris Thielemans.
Published:10 May 2021Article ID:20200205.
https://doi.org/10.1098/rsta.2020.0205.

Synergistic multi-contrast cardiac magnetic resonance image reconstruction.
Haikun Qi, Gastao Cruz, René Botnar and Claudia Prieto.
Published:10 May 2021Article ID:20200197.
https://doi.org/10.1098/rsta.2020.0197.

Physics-based reconstruction methods for magnetic resonance imaging.
Xiaoqing Wang, Zhengguo Tan, Nick Scholand, Volkert Roeloffs and Martin Uecker.
Published:10 May 2021Article ID:20200196.
https://doi.org/10.1098/rsta.2020.0196.

Improved identification of abdominal aortic aneurysm using the Kernelized Expectation Maximization algorithm.
Daniel Deidda, Mercy I. Akerele, Robert G. Aykroyd, Marc R. Dweck, Kelley Ferreira, Rachael O. Forsythe, Warda Heetun, David E. Newby, Maaz Syed and Charalampos Tsoumpas.
Published:10 May 2021Article ID:20200201.
https://doi.org/10.1098/rsta.2020.0201.

Which GAN? A comparative study of generative adversarial network-based fast MRI reconstruction.
Jun Lv, Jin Zhu and Guang Yang.
Published:10 May 2021Article ID:20200203.
https://doi.org/10.1098/rsta.2020.0203.

Evaluation of synergistic image registration for motion-corrected coronary NaF-PET-MR.
Johannes Mayer, Yining Jin, Thomas-Heinrich Wurster, Marcus R. Makowski and Christoph Kolbitsch.
Published:10 May 2021Article ID:20200202.
https://doi.org/10.1098/rsta.2020.0202.

Regularization by denoising sub-sampled Newton method for spectral CT multi-material decomposition.
Alessandro Perelli and Martin S. Andersen.
Published:10 May 2021Article ID:20200191.
https://doi.org/10.1098/rsta.2020.0191.

Fusing electrical and elasticity imaging.
Andreas Hauptmann and Danny Smyl.
Published:10 May 2021Article ID:20200194.
https://doi.org/10.1098/rsta.2020.0194.