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Improved compressed sensing reconstruction for \(^{19}\)F magnetic resonance imaging

  • Thomas KampfEmail author
  • Volker J. F. Sturm
  • Thomas C. Basse-Lüsebrink
  • André Fischer
  • Lukas R. Buschle
  • Felix T. Kurz
  • Heinz-Peter Schlemmer
  • Christian H. Ziener
  • Sabine Heiland
  • Martin Bendszus
  • Mirko Pham
  • Guido Stoll
  • Peter M. Jakob
Research Article

Abstract

Objective

In magnetic resonance imaging (MRI), compressed sensing (CS) enables the reconstruction of undersampled sparse data sets. Thus, partial acquisition of the underlying k-space data is sufficient, which significantly reduces measurement time. While 19F MRI data sets are spatially sparse, they often suffer from low SNR. This can lead to artifacts in CS reconstructions that reduce the image quality. We present a method to improve the image quality of undersampled, reconstructed CS data sets.

Materials and methods

Two resampling strategies in combination with CS reconstructions are presented. Numerical simulations are performed for low-SNR spatially sparse data obtained from 19F chemical-shift imaging measurements. Different parameter settings for undersampling factors and SNR values are tested and the error is quantified in terms of the root-mean-square error.

Results

An improvement in overall image quality compared to conventional CS reconstructions was observed for both strategies. Specifically spike artifacts in the background were suppressed, while the changes in signal pixels remained small.

Discussion

The proposed methods improve the quality of CS reconstructions. Furthermore, because resampling is applied during post-processing, no additional measurement time is required. This allows easy incorporation into existing protocols and application to already measured data.

Keywords

19MRI CSI MRSI Compressed sensing Sparse Artifact 

Notes

Acknowledgements

This work was partially supported by the Deutsche Forschungsgemeinschaft SFB 630 (C2) and SFB 688 (B 5), Deutsche Forschungsgemeinschaft (contract grant number: DFG ZI 1295/2-1 and DFG KU 3555/1-1). L. R. Buschle was supported by a scholarship of the German Academic Scholarship Foundation (Studienstiftung des deutschen Volkes). F. T. Kurz was supported by a postdoctoral fellowship from the medical faculty of Heidelberg University and the Hoffmann-Klose foundation of Heidelberg University. V.J.F Sturm was supported by the German Research Council (DFG, SFB 1118/2).

Compliance with ethical standards

Conflict of interest

TBL is currently employed by Bruker BioSpin MRI GmbH, Ettlingen, Germany. AF is currently employed by GE Healthcare. However, the main part of their contribution to this work steems from their time at the department of EP5, Würzburg, Germany.

Ethical approval

All animal experiments presented in this work were performed according to institutional guidelines and were approved by the Ethics Committee for Animal Welfare of the University Hospital of Würzburg, Germany.

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Copyright information

© European Society for Magnetic Resonance in Medicine and Biology (ESMRMB) 2019

Authors and Affiliations

  • Thomas Kampf
    • 1
    • 2
    Email author
  • Volker J. F. Sturm
    • 3
  • Thomas C. Basse-Lüsebrink
    • 2
  • André Fischer
    • 2
  • Lukas R. Buschle
    • 4
  • Felix T. Kurz
    • 3
    • 4
  • Heinz-Peter Schlemmer
    • 4
  • Christian H. Ziener
    • 4
  • Sabine Heiland
    • 3
  • Martin Bendszus
    • 5
  • Mirko Pham
    • 1
  • Guido Stoll
    • 6
  • Peter M. Jakob
    • 2
  1. 1.Department of NeuroradiologyUniversity Hospital WürzburgWürzburgGermany
  2. 2.Experimental Physics VUniversity of WürzburgWürzburgGermany
  3. 3.Experimental NeuroradiologyUniversity Hospital HeidelbergHeidelbergGermany
  4. 4.German Cancer Research CenterHeidelbergGermany
  5. 5.Department of NeuroradiologyUniversity Hospital HeidelbergHeidelbergGermany
  6. 6.Department of NeurologyUniversity Hospital WürzburgWürzburgGermany

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