Iterative Adaptive Sparse Sampling Method for Magnetic Resonance Imaging

Giuseppe Placidi, Luigi Cinque, Andrea Petracca, Matteo Polsinelli, Matteo Spezialetti

2017

Abstract

Magnetic Resonance Imaging (MRI) represents a major imaging modality for its low invasiveness and for its property to be used in real-time and functional applications. The acquisition of radial directions is often used but a complete examination always requires long acquisition times. The only way to reduce acquisition time is undersampling. We present an iterative adaptive acquisition method (AAM) for radial sampling/reconstruction MRI that uses the information collected during the sequential acquisition process on the inherent structure of the underlying image for calculating the following most informative directions. A full description of AAM is furnished and some experimental results are reported; a comparison between AAM and weighted compressed sensing (CS) strategy is performed on numerical data. The results demonstrate that AAM converges faster than CS and that it has a good termination criterion for the acquisition process.

Paper Citation

in Harvard Style

Placidi G., Cinque L., Petracca A., Polsinelli M. and Spezialetti M. (2017). Iterative Adaptive Sparse Sampling Method for Magnetic Resonance Imaging . In Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM, ISBN 978-989-758-222-6, pages 510-518. DOI: 10.5220/0006199105100518

in Bibtex Style

@conference{icpram17,
author={Giuseppe Placidi and Luigi Cinque and Andrea Petracca and Matteo Polsinelli and Matteo Spezialetti},
title={Iterative Adaptive Sparse Sampling Method for Magnetic Resonance Imaging},
booktitle={Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,},
year={2017},
pages={510-518},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006199105100518},
isbn={978-989-758-222-6},
}

in EndNote Style

TY - CONF
JO - Proceedings of the 6th International Conference on Pattern Recognition Applications and Methods - Volume 1: ICPRAM,
TI - Iterative Adaptive Sparse Sampling Method for Magnetic Resonance Imaging
SN - 978-989-758-222-6
AU - Placidi G.
AU - Cinque L.
AU - Petracca A.
AU - Polsinelli M.
AU - Spezialetti M.
PY - 2017
SP - 510
EP - 518
DO - 10.5220/0006199105100518