International Journal on Magnetic Particle Imaging
Vol 6 No 2 Suppl. 1 (2020)
https://doi.org/10.18416/IJMPI.2020.2009002

Proceedings Articles

A sparse row-action algorithm for Magnetic Particle Imaging

Main Article Content

Florian Lieb (Aschaffenburg University of Applied Sciences), Tobias Knopp 

Abstract

The image reconstruction in Magnetic Particle Imaging (MPI) relies on efficiently solving an ill-posed inverse problem. Current state-of-the-art reconstruction methods are either based on row-action methods with fast convergence but limited noise suppression or advanced sparsity constraints showing better image quality, but suffering from a higher computational complexity and slower convergence. In this contribution, we propose a novel row-action framework where advanced sparsity constraints, e.g., a combination of L1- and TV-norm, can be included. Its performance is numerically evaluated on simulated and real MPI data, showing a significant reduction of computation time while retaining the enhanced imaging quality.  
 
Int. J. Mag. Part. Imag. 6(2), Suppl. 1, 2020, Article ID: 2009002, DOI: 10.18416/IJMPI.2020.2009002

Article Details