In this blog post Sri Kashyap and I describe how to deal with the registration of high-resolution datasets across days, across different resolutions, and across different sequences.
I am particularly fond of the following two tools: Firstly, ITK-SNAP for visually-guided manual alignment and secondly, using ANTs programs: antsRegistration and antsApplyTransforms.
Maximum intensity projection and minimum intensity projection can be insightful for mapping of vessels in 3D-slabs. In this post, I describe the application of intensity projections with LAYNII.
CBV-fMRI with VASO is highly dependent on a good inversion contrast. It gives it its CBV sensitivity and is also responsible for most of the VASO specific pitfalls (e.g. inflow, CSF etc. ). And thus, it should be optimized as much as possible.
In this blog post, I want to describe the most important features of a reliable inversion pulse for the application of VASO at 7T with a head transmit coil.
Continue reading “TR-FOCI pulse optimisations for SS-SI VASO”
ISIS-conv is a very useful dicom to nii converter from Enrico Reimer. ISIS-conv gets along with a lot of challenging data sets that no other converter (that I know of) can handle so conveniently:
There is a Mac-installation package of ISIS-conv. Unfortunately, however, with every IOS update, it has become more complicated to install it.
Since, I spend too much time figuring out how to install it after every update, I am collecting the necessary steps in this Blog post for future reference:
In this blog post, I want to describe the application and working principle of a few spatial smoothing algorithms that are implemented in LAYNII.
LN_GRADSMOOTHLN_LAYERSMOOTHLN_LAYERSMOOTHLN_DIRECT_SMOOTHLN_TEMPSMOOTHIn this Blog post, I seek to describe a quick example of how to analyze high-resolution data across layers and columns with LAYNII.
Continue reading “Quick example of cortical unfolding in LAYNII”
In the last years, I and multiple other VASO users have encountered many occasions of voxels that show negative CBV change (positive VASO signal change) while the BOLD suggests that the activation should be positive. In this blog post, I want to list potential sources of this surprising effect.
In this blog-post I want to describe a setup, how you can include an additional ICE functor in your reconstruction pipeline that sends raw Twix files from the Reconstruction computer to any given custom server. Continue reading “How send raw k-space data to any given server with Twix or with a modified ICE-chain”
Recently, my adviser Peter Bandettini asked me to compile a list of all potential applications for layer-fMRI. It was a fun exercise to think about it. Below, you find a list of all potential applications that I could think of. Continue reading “List of potential layer-fMRI application studies”
In this blogpost I describe how to install the DTI-TK NIfTI quicklook plugin for nii files for mac OS.
In this blog post, I want to write about pipelines on how to prepare Nifti-brain data and make them printable by a 3D-printer.
Two pipelines are shown. One pipeline describes the 3D-printing the cortical folding structure that is estimated with Freesurfer and subsequently corrected with Meshlab. And another pipeline describes how you can 3D-print any binary nii-volume by using the AFNI-program IsoSurface and correct the output with netfabb. Continue reading “3D-printing nii data”
Often we would like to normalize depth-dependent fMRI signals and assign it to specific cytoarchitectonially defined cortical layers. However, we often only have access to cytoarchitectonial histology data in the form to figures in papers. But since we only have the web-view or the PDF available, we cannot easily extract those data as a layer-profile. Since most layering tools are designed for nii data only, paper figures (e.g. jpg or GNP) are not straight-forwardly transformed to layer profiles.
In this blob post, I describe a set of steps on how to convert any paper figure into a nii-file that allows the extraction of layer profiles.
Continue reading “How to convert any paper figure into a layer-profile”
In this blog post I want to discuss how the tSNR in sub-millimeter fMRI can be substantially improved by optimizing the GRAPPA regularization. Adjusting one single GRAPPA reconstruction parameter can almost double the tSNR of your fMRI time series. With almost no penalty.
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
Continue reading “Documentation of Installing an IDEA VirtualBox for VE11 from OVA”
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.
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:
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.
Continue reading “Unwanted spatial blurring during resampling”
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.
Continue reading “Partial-Fourier imaging at High Resolutions”
Smoothing within layers can be advantageous for multiple reasons:
