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Magnetic Resonance Fingerprinting
MR Fingerprinting (MRF) is a new approach of MRI, where unique NMR tissue signatures (“MR Fingerprints”) are collected to provide simultaneous, quantitative maps of most essential MRI markers used routinely in clinical practice.
Magnetic Resonance Fingerprinting (MRF) [1] allows for the simultaneous quantification of multiple tissue properties of a material or tissue by creating a rapid time series of images, whose contrast and signal are strongly affected by the details of the imaging parameters (i.e. the choice of flip angle FA and repetition time TR) and the intrinsic NMR properties of the imaged object (e.g. longitudinal and transverse relaxation T1 and T2, off resonance). Initial development of MRF [1] relies on the pseudo-random selection of large (n=300-1000) [1-3] FA and TR schedules in order to collect MR fingerprints. A dictionary of complex NMR signals is computed offline based on the Bloch equations framework, and full quantification is obtained from pattern matching of the MR Fingerprints with the dictionary.
The focus of our work at the Cardiovascular Magnetic Resonance Group (CMR, Institute for Biomedical Engineering, ETH Zurich) and the Quantitative Biomedical Imaging Group (QBIG, Department of Biomedical Engineering, University Basel) lies on the development and implementation of advanced imaging modalities for MRI that allows for quantitative imaging within clinically acceptable scan times. To this end, we cover a broad range of expertise from theoretical description and implementation of new MRI sequences, to the development of acquisition and image reconstruction pipelines, and ultimately verification in realistic phantoms and in-vivo datasets.
**References**
1. Ma, D. et.al, Magnetic Resonance Fingerprinting, Nature, 2013, 495(7440), 187–192.
2. Jiang, Y. et al., MR Fingerprinting Using Fast Imaging with Steady State Precession (FISP) with Spiral Readout, Magnetic Resonance in Medicine, 2014, 74(6), 1621-1631.
3. Ye, H. et al., Simultaneous Multislice Magnetic Resonance Fingerprinting (SMS-MRF) With Direct-Spiral Slice-GRAPPA (ds-SG) Reconstruction, Magnetic Resonance in Medicine, 2016, in press.
Magnetic Resonance Fingerprinting (MRF) [1] allows for the simultaneous quantification of multiple tissue properties of a material or tissue by creating a rapid time series of images, whose contrast and signal are strongly affected by the details of the imaging parameters (i.e. the choice of flip angle FA and repetition time TR) and the intrinsic NMR properties of the imaged object (e.g. longitudinal and transverse relaxation T1 and T2, off resonance). Initial development of MRF [1] relies on the pseudo-random selection of large (n=300-1000) [1-3] FA and TR schedules in order to collect MR fingerprints. A dictionary of complex NMR signals is computed offline based on the Bloch equations framework, and full quantification is obtained from pattern matching of the MR Fingerprints with the dictionary.
The focus of our work at the Cardiovascular Magnetic Resonance Group (CMR, Institute for Biomedical Engineering, ETH Zurich) and the Quantitative Biomedical Imaging Group (QBIG, Department of Biomedical Engineering, University Basel) lies on the development and implementation of advanced imaging modalities for MRI that allows for quantitative imaging within clinically acceptable scan times. To this end, we cover a broad range of expertise from theoretical description and implementation of new MRI sequences, to the development of acquisition and image reconstruction pipelines, and ultimately verification in realistic phantoms and in-vivo datasets.
**References**
1. Ma, D. et.al, Magnetic Resonance Fingerprinting, Nature, 2013, 495(7440), 187–192. 2. Jiang, Y. et al., MR Fingerprinting Using Fast Imaging with Steady State Precession (FISP) with Spiral Readout, Magnetic Resonance in Medicine, 2014, 74(6), 1621-1631. 3. Ye, H. et al., Simultaneous Multislice Magnetic Resonance Fingerprinting (SMS-MRF) With Direct-Spiral Slice-GRAPPA (ds-SG) Reconstruction, Magnetic Resonance in Medicine, 2016, in press.
The following list of possible student projects serves as a general guideline but can be adjusted to the background and interest of the students. Please contact Christian Guenthner guenthner@biomed.ee.ethz.ch (ETH Zurich) or Mathieu Sarracanie mathieu.sarracanie@unibas.ch (University Basel) if you are interested. Possible student projects include
- Design and evaluation of optimization algorithms for MRF
- Theoretical frameworks to investigate MRF robustness to noise and potential confounding factors
- Transfer and evaluation of optimized MRF on clinical MRI scanners
- Implementation of MRI acceleration techniques to speed-up MRF (under sampling, multi-band, parallel imaging)
The following list of possible student projects serves as a general guideline but can be adjusted to the background and interest of the students. Please contact Christian Guenthner guenthner@biomed.ee.ethz.ch (ETH Zurich) or Mathieu Sarracanie mathieu.sarracanie@unibas.ch (University Basel) if you are interested. Possible student projects include
- Design and evaluation of optimization algorithms for MRF - Theoretical frameworks to investigate MRF robustness to noise and potential confounding factors - Transfer and evaluation of optimized MRF on clinical MRI scanners - Implementation of MRI acceleration techniques to speed-up MRF (under sampling, multi-band, parallel imaging)
Interested students are asked to apply with a CV and a transcript of records. For students from abroad, we also need to know how they plan to organize funding for their stay.
- Christian Günthner, guenthner@biomed.ee.ethz.ch, ETZ F61.2, Tel.: +41 44 633 89 50
- Mathieu Sarracanie, mathieu.sarracanie@unibas.ch
- _Supervising Professor_: Sebastian Kozerke
Interested students are asked to apply with a CV and a transcript of records. For students from abroad, we also need to know how they plan to organize funding for their stay. - Christian Günthner, guenthner@biomed.ee.ethz.ch, ETZ F61.2, Tel.: +41 44 633 89 50 - Mathieu Sarracanie, mathieu.sarracanie@unibas.ch