Published March 22, 2022 | Version v1
Dataset Open

MR Gradient System Long-Term Stability Investigation and Protocol Optimization for Quality Control using Gradient Impulse Response Function (GIRF)

Authors/Creators

  • 1. University Health Network
  • 2. Norwegian University of Science and Technology
  • 3. University of British Columbia

Contributors

Data collector:

  • 1. University Health Network

Description

The dataset of the abstract "MR Gradient System Long-Term Stability Investigation and Protocol Optimization for Quality Control using Gradient Impulse Response Function (GIRF)" for ISMRM 2022, London, UK. The data processing code with instructions could be found here.

 

Meas1.zip and Meas2.zip contain the first and the second measurements of the raw T2* decay signal acquired with the phantom-based method. Note that the coil dimension has been averaged to save data volume for demonstration purposes. This will lead to a lower SNR of the calculated output gradient and GIRF.

 

CalculatedGIRF.zip provides the author's pre-calculated GIRFs using the data without coil averaging. This data is used for all the postprocessing (e.g. SNR and stability analysis, etc.) in the published abstract with the source code provided in the same Github repository.

 

Files

CalculatedGIRF.zip

Files (1.2 GB)

Name Size
md5:edb6dced30c3c11a2992a97a9661f5a3
90.7 MB Preview Download
md5:9cc101f3f1891f1cc3ca8bc362a39fc0
384.2 MB Preview Download
md5:7512c1847f19e638962325e9a2455a1b
755.6 MB Preview Download

Additional details

References

  • Duyn, J. H., Yang, Y., Frank, J. a, & van der Veen, J. W. (1998). Simple Correction Method fork-Space Trajectory Deviations in MRI. Journal of Magnetic Resonance, 132(1), 150–153. https://doi.org/10.1006/jmre.1998.1396
  • Vannesjo, S. J., Haeberlin, M., Kasper, L., Pavan, M., Wilm, B. J., Barmet, C., & Pruessmann, K. P. (2013). Gradient system characterization by impulse response measurements with a dynamic field camera. Magnetic Resonance in Medicine, 69(2), 583–593. https://doi.org/10.1002/mrm.24263
  • Graedel, N. N., Hurley, S. A., Clare, S., Miller, K., Pruessmann, K. P., & Vannesjo, S. J. (2017). Comparison of gradient impulse response functions measured with a dynamic field camera and a phantombased technique. ESMRMB 2017, 34th Annual Scientific Meeting, Barcelona, ES, October 19–October 21: Abstracts, Saturday, 30(S1), 343–499. https://doi.org/10.1007/s10334-017-0634-z
  • Vannesjo, S. J., Graedel, N. N., Kasper, L., Gross, S., Busch, J., Haeberlin, M., Barmet, C., & Pruessmann, K. P. (2016). Image reconstruction using a gradient impulse response model for trajectory prediction. Magnetic Resonance in Medicine, 76(1), 45–58. https://doi.org/10.1002/mrm.25841
  • Stich, M., Wech, T., Slawig, A., Ringler, R., Dewdney, A., Greiser, A., Ruyters, G., Bley, T. A., & Köstler, H. (2018). Gradient waveform pre-emphasis based on the gradient system transfer function. Magnetic Resonance in Medicine, 80(4), 1521–1532. https://doi.org/10.1002/mrm.27147
  • Robison, R. K., Li, Z., Wang, D., Ooi, M. B., & Pipe, J. G. (2019). Correction of B0 eddy current effects in spiral MRI. Magnetic Resonance in Medicine, 81(4), 2501–2513. https://doi.org/10.1002/mrm.27583