Documentation of Installing an IDEA VirtualBox for VE11 from OVA

This post documents the installation of an IDEA VE11 virtual box on a mac as done on May 14th 2018

Big thanks to Andy for figuring out how this works

Prerequisites

  • Here I start with a already built images of IDEA on windows vista and mars on Ubuntu. the images from FMRIF can be taken from erbium.nimh.nih.gov:/fmrif/projects/SiemensIdea/virtual_machines/OVF/): IDEA_ve11c-mars.ova and IDEA_ve11c+vd13d+vd13a.ova
  • Virtual box software can be downloaded here.

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EPI phase correction algorithms

At high resolution EPI, the gradients are pushed to their limits and the ramp sampling ratio is particularly large. This means that the ghosting is increased and the Nyquist ghost correction is getting more important. In this post, I describe how to change the Nyquist ghost correction algorithm.

Phase_correction.gif
The high ramp sampling ratio in high-resolution EPI results in larger ghosts. Changing the correction algorithm from “normal” to “local” can help a lot.

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SS-SI VASO pitfalls in visual cortex

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Activation maps for BOLD and VASO. At about 0.8 mm resolution, one starts to see that VASO is less sensitive to large draining veins.

With respect to high-resolution VASO application, visual cortex is very unique. I found it to be a challenging area. However, because of its high demand, I have been working on is with multiple collaborators. The most important pitfalls of SS-SI VASO in visual cortex that I came across in these collaborations are discussed below.

The take home message tat I learned from manny experiments is:

  1. Use axial slices with the phase encoding direction A>>P.
  2. Watch out for negative voxels.
  3. Invest a lot of effort in optimizing GRAPPA parameters, its worth it.

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Unwanted spatial blurring during resampling

In layer-fMRI, we spend so much time and effort to achieve high spatial resolutions and small voxel sizes during the acquisition. However, during the evaluation pipeline much of this spatial resolution can be lost during multiple resampling steps.

In this post, I want to discuss sources of signal blurring during spatial resampling steps and potential strategies to account for them.

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