Iterative Adaptive Sparse Sampling Method for Magnetic Resonance Imaging

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

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.

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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