This post contains a collection of recently presented powerpoint slides.
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
- 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.
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.
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.
This blog post discusses the resolution loss when applying partial-Fourier imaging in GE-EPI in the presence of strong T2*-decay.
I found that that when I was aiming for high-resolutions, it is beneficial to refrain from the application of partial Fourier (PF) imaging as much as possible. For the long readout durations at high-resolutions and the fast T2/T2*-decay at high field strengths results in even stronger blurring of partial-Fourier.
Smoothing within layers can be advantageous for multiple reasons:
- Increasing the CNR without loosing spatial information across cortical depths.
- Visualization of striping pattern across columnar structures.
- Avoiding leakage of physiological noise from CSF space into GM tissue.