13 Apr 2022
online event


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Discussion points of the webinar:

  • What are the principal advantages of spirals for high-resolution imaging?
  • What components are required for high-quality spiral imaging?
  • How do I get started with spiral imaging and reconstruction?

Relevant Literature:

  • Kasper, L., Engel, M., Barmet, C., Haeberlin, M., Wilm, B.J., Dietrich, B.E., Schmid, T., Gross, S., Brunner, D.O., Stephan, K.E., Pruessmann, K.P., 2018. Rapid anatomical brain imaging using spiral acquisition and an expanded signal model. NeuroImage 168, 88–100.
  • Kasper, L., Engel, M., Heinzle, J., Mueller-Schrader, M., Graedel, N.N., Reber, J., Schmid, T., Barmet, C., Wilm, B.J., Stephan, K.E., Pruessmann, K.P., 2022. Advances in spiral fMRI: A high-resolution study with single-shot acquisition. NeuroImage 246, 118738.
  • Engel, M., Kasper, L., Barmet, C., Schmid, T., Vionnet, L., Wilm, B., Pruessmann, K.P., 2018. Single-shot spiral imaging at 7 T. Magnetic Resonance in Medicine 80, 1836–1846.
  • Graedel, N.N., Kasper, L., Engel, M., Nussbaum, J., Wilm, B.J., Pruessmann, K.P., Vannesjo, S.J., 2021. Feasibility of spiral fMRI based on an LTI gradient model. NeuroImage 245, 118674.
  • Wilm, B.J., Barmet, C., Pavan, M., Pruessmann, K.P., 2011. Higher order reconstruction for MRI in the presence of spatiotemporal field perturbations. Magnetic Resonance in Medicine 65, 1690–1701.

Lars Kasper, PhD, Scientific Associate

BRAIN-TO lab (“Brain Research in Advanced Imaging and Neuromodeling – Toronto”)

Lars received his PhD in Biomedical Engineering from ETH Zurich in 2014, with a work on "Noise Reduction in fMRI Utilizing Concurrent Magnetic Field Monitoring". During his postdoctoral research in the MR Methods and Technology Group (Klaas Pruessmann) and Translational Neuromodeling Unit (Klaas Stephan) in Zurich, Lars was working at the interface between cutting-edge imaging concepts and their applications in computational neuroscience and psychiatry. In particular, Lars' projects included ultra-high field spiral MRI and NMR-probe based field monitoring in the context of fMRI, as well as laminar fMRI applications to investigate prediction error signaling according to the Bayesian Brain hypothesis. Since 2020, Lars is a scientific associate in Kamil Uludag's lab for Brain Research in Advanced Imaging and Neuromodeling - Toronto (BRAIN-TO), focusing on the translation of promising MR sequence and reconstruction concepts into the clinics, e.g., for spiral diffusion MRI. Lars' core interest is improving image and time series quality in MRI through understanding both numerator and denominator of the signal-to-noise ratio, i.e., optimizing sampling in MRI, as well as characterizing and correcting for the various physiological and system-induced noise sources. Lars is a fervent supporter of open and accessible neuroscience, and contributes through clean code in the form of usable toolboxes (PhysIO for physiological noise correction in fMRI, UniQC for unified image quality control in MR development), as well as the family committee of the ISMRM.