Back to Search Start Over

Synergistic tomographic image reconstruction: part 2

Authors :
Christoph Kolbitsch
Jakob Sauer Jørgensen
Kris Thielemans
Charalampos Tsoumpas
Source :
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, Tsoumpas, C, Sauer Jørgensen, J, Kolbitsch, C & Thielemans, K 2021, ' Synergistic tomographic image reconstruction: part 2 ', Philosophical transactions. Series A, Mathematical, physical, and engineering sciences, vol. 379, no. 2204, 20210111 . https://doi.org/10.1098/rsta.2021.0111
Publication Year :
2021
Publisher :
The Royal Society Publishing, 2021.

Abstract

This special issue is the second part of a themed issue that focuses on synergistic tomographic image reconstruction and includes a range of contributions in multiple disciplines and application areas. The primary subject of study lies within inverse problems which are tackled with various methods including statistical and computational approaches. This volume covers algorithms and methods for a wide range of imaging techniques such as spectral X-ray computed tomography (CT), positron emission tomography combined with CT or magnetic resonance imaging, bioluminescence imaging and fluorescence-mediated imaging as well as diffuse optical tomography combined with ultrasound. Some of the articles demonstrate their utility on real-world challenges, either medical applications (e.g. motion compensation for imaging patients) or applications in material sciences (e.g. material decomposition and characterization). One of the desired outcomes of the special issues is to bring together different scientific communities which do not usually interact as they do not share the same platforms such as journals and conferences. This article is part of the theme issue ‘Synergistic tomographic image reconstruction: part 2’.

Details

Language :
English
ISSN :
14712962 and 1364503X
Volume :
379
Issue :
2204
Database :
OpenAIRE
Journal :
Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Accession number :
edsair.doi.dedup.....ceea5aa7b43440b2bd0b1f33df9367f1
Full Text :
https://doi.org/10.1098/rsta.2021.0111