Multi-channel Potts-based reconstruction for multi-spectral computed tomography

We consider reconstructing multi-channel images from measurements performed by photon-counting and energy-discriminating detectors in the setting of multi-spectral x-ray computed tomography (CT). Our aim is to exploit the strong structural correlation that is known to exist between the channels of m...

Full description

Saved in:
Bibliographic Details
Main Authors: Kiefer, Lukas (Author) , Petra, Stefania (Author) , Storath, Martin (Author) , Weinmann, Andreas (Author)
Format: Article (Journal)
Language:English
Published: 1 March 2021
In: Inverse problems
Year: 2021, Volume: 37, Issue: 4, Pages: ?
ISSN:1361-6420
DOI:10.1088/1361-6420/abdd45
Online Access:Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1088/1361-6420/abdd45
Get full text
Author Notes:Lukas Kiefer, Stefania Petra, Martin Storath and Andreas Weinmann
Description
Summary:We consider reconstructing multi-channel images from measurements performed by photon-counting and energy-discriminating detectors in the setting of multi-spectral x-ray computed tomography (CT). Our aim is to exploit the strong structural correlation that is known to exist between the channels of multi-spectral CT images. To that end, we adopt the multi-channel Potts prior to jointly reconstruct all channels. This nonconvex prior produces piecewise constant solutions with strongly correlated channels. In particular, edges are strictly enforced to have the same spatial position across channels which is a benefit over TV-based methods whose channel-couplings are typically less strict. We consider the Potts prior in two frameworks: (a) in the context of a variational Potts model, and (b) in a Potts-superiorization approach that perturbs the iterates of a basic iterative least squares solver. We identify an alternating direction method of multipliers approach as well as a Potts-superiorized conjugate gradient method as particularly suitable. In numerical experiments, we compare the Potts prior based approaches to existing TV-type approaches on realistically simulated multi-spectral CT data and obtain improved reconstruction for compound solid bodies.
Item Description:Gesehen am 06.08.2021
Physical Description:Online Resource
ISSN:1361-6420
DOI:10.1088/1361-6420/abdd45