Super-resolution methods in MRI: Can they improve the trade-off between resolution, signal-to-noise ratio, and acquisition time?

Authors

  • Esben Plenge,

    Corresponding author
    1. Department of Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center, Rotterdam, Rotterdam, The Netherlands
    2. Department of Radiology, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
    • Departments of Medical Informatics and Radiology, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center Rotterdam, P. O. Box 2040, 3000 CA Rotterdam, The Netherlands
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  • Dirk H. J. Poot,

    1. Department of Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center, Rotterdam, Rotterdam, The Netherlands
    2. Department of Radiology, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
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  • Monique Bernsen,

    1. Department of Radiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
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  • Gyula Kotek,

    1. Department of Radiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
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  • Gavin Houston,

    1. Department of Radiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
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  • Piotr Wielopolski,

    1. Department of Radiology, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
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  • Louise van der Weerd,

    1. Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands
    2. Department of Human Genetics, Leiden University Medical Center, Leiden, The Netherlands
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  • Wiro J. Niessen,

    1. Department of Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center, Rotterdam, Rotterdam, The Netherlands
    2. Department of Radiology, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
    3. Quantitative Imaging Group, Department of Imaging Science & Technology, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands
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  • Erik Meijering

    1. Department of Medical Informatics, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center, Rotterdam, Rotterdam, The Netherlands
    2. Department of Radiology, Biomedical Imaging Group Rotterdam, Erasmus MC – University Medical Center Rotterdam, Rotterdam, The Netherlands
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Abstract

Improving the resolution in magnetic resonance imaging comes at the cost of either lower signal-to-noise ratio, longer acquisition time or both. This study investigates whether so-called super-resolution reconstruction methods can increase the resolution in the slice selection direction and, as such, are a viable alternative to direct high-resolution acquisition in terms of the signal-to-noise ratio and acquisition time trade-offs. The performance of six super-resolution reconstruction methods and direct high-resolution acquisitions was compared with respect to these trade-offs. The methods are based on iterative back-projection, algebraic reconstruction, and regularized least squares. The algorithms were applied to low-resolution data sets within which the images were rotated relative to each other. Quantitative experiments involved a computational phantom and a physical phantom containing structures of known dimensions. To visually validate the quantitative evaluations, qualitative experiments were performed, in which images of three different subjects (a phantom, an ex vivo rat knee, and a postmortem mouse) were acquired with different magnetic resonance imaging scanners. The results show that super-resolution reconstruction can indeed improve the resolution, signal-to-noise ratio and acquisition time trade-offs compared with direct high-resolution acquisition. Magn Reson Med, 2012. © 2012 Wiley Periodicals, Inc.

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