This post lists the background material of the hands-on tutorial about high-resolution EPI on SIEMENS scanners.
Content and references during the tutorial
- 0:00 Introduction of this tutorial
- 0:57 Introduction to EPI
- 2:32 Data to download: OpenNeuro (brows to the Workshop files)
- 4:22 Optimized localizer for high-contrast T1: Pdfs of protocols
- 10:23 Access to hidden recon parameters in IceConfig
- 12:48 Changing IcePat parameters
- 16:32 GRAPPA regularization strengths: Blog post with further information
- 20:35 GRAPPA kernel size: Blog post with further information
- 28:03 Bandwidth of EPI: Blog post with further information
- 26:57 GRAPPA calibration data scheme: Paper on FLEET and FLASH GRAPPA
- 41:56 B0-related artifacts
- 47:03 Retrospective reconstruction
- 51:56 Phase correction algorithm: Blog post with further information
- 57:11 Magnitude phase and real part
- 58:18 Coil uncombined images
- 59:48 Acknowledgements
This tutorial is done in context of the 2019, Minnesota Workshop on Ultra high field MRI, Namely the Educational course on layer-fMRI organized by Cheryl Olman: https://www.cmrr.umn.edu/workshop2019/
The slides can be downloaded here: https://layerfmri.page.link/CMRR_2019_scanning
They are acquired at Scannexus and at SFIM.
The time series analysis shown in the slides was done in AFNI:
3dTstat -prefix MEAN.nii -mean overwrite Timeseries.nii'[0..$(2)]'
3dTstat -prefix tSNR.nii -tSNR overwrite Timeseries.nii'[0..$(2)]'
Other layer-fMRI tutorials:
- I thank Robin Heidemann for tips regarding the ImprovedGrappaWs and the GRAPPA Kernel size.
- I thank Markus Streicher for tips about the phase correction options.
- I thank Peter Koopmanns for tips regarding the PF reconstruction with POCS.
- I thank Kawin Setsompop for tips regarding the number of POCS iterations.
- I thank Jonathan Polimeni for tips about the regularization strength in the GRAPPA Kernel fit.
- I thank Andreas Schäfer for tips on complex values uncombined reconstruction.
- I thanks Sean Marrett for the inspiration to make this tutorial.
- I thanks Benedikt Poser for everything else.