# 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