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1. Generally you should be fine to port it into other softwares. However, we can’t claim complete knowledge or responsibility over what is being done by other tools outside of BrainSuite so you will have to use your best judgement to figure out the right steps to take for your study.
2. It may be possible to use our registration-based distortion correction on BOLD images as the method is based on the physics of EPI distortion. However, applying this method on BOLD images has not been properly tested or examined by BrainSuite so we can’t make any guarantees on the performance. It’s absolutely worth giving it a try. The full description of the methods can be found here: Bhushan, Chitresh, et al. “Co-registration and distortion correction of diffusion and anatomical images based on inverse contrast normalization.” Neuroimage 115 (2015): 269-280.
You can find the source code for BDP here: http://forums.brainsuite.org/download/
or you can try to hack the command line tool by inputting dummy bvec and bval files, just making sure you have the right number of values to match the number of volumes in your BOLD images. Also at least one of the bvalues should equal to 0 since it the b=0 image is used as the reference image for the registration template.
If you give it a try, please let me know how it goes by replying on this thread. Very interested!
Good luck!December 5, 2019 at 2:19 pm in reply to: Cortical_Area_mid，Cortical_Area_inner，Cortical_Area_pial #1993
Midcortex is essentially the average of the inner and pial cortex. The inner cortex would sit along the grey-white junction while the pial cortex lines the surface of the brain. Therefore, the midcortex runs along the middle of the cortical ribbon.December 5, 2019 at 12:17 pm in reply to: Cortical_Area_mid，Cortical_Area_inner，Cortical_Area_pial #1990
They are the surface areas for each respective surfaces: midcortex, inner cortex, and the pial cortex.
There exists some nice studies that show that cortical surface area, pial cortex in particular, can be more sensitive to detecting differences/changes in disease in comparison to cortical thickness.
Additionally, this measure is highly correlated to grey matter volume. In my opinion, this measure may be really useful if in your dataset does not have great contrast and great tissue classification but are getting more reliable surface extractions.
Hope you find this useful.
- This reply was modified 7 months, 1 week ago by sychoi.
Under Cortex–>Select SVReg directory
select the directory <brainsuite directory>\<brainsuite version>\svreg
for example on Windows: C:\Program Files\BrainSuite19a\svreg
or mac: /Applications/BrainSuite19a/svreg
I’m sorry I don’t think we provide what you are looking for. There are 2 xml files included with the download for ROI and sulcal description but does not have information on the coordinates of those regions.
Thank you for using BrainSuite.
The short answer is no.
If a diffusion modeling flag is not indicated then BDP will calculate tensors by default.
BDP (BrainSuite Diffusion Pipeline) is a commandline tool only.
sorry about that.
you’re correct in that you need t1 images to run svreg since you need to first run CSE
There’s no way to do automated segmentation on diffusion images alone on brainsuite. If you have label files made elsewhere as long as you have the correct file format, you can load the label file and create a connectivity graph that way.
If you have further questions on the connectivity graph, please open up a new topic.
Unfortunately, you can only perform cortical extraction on T1 weighted images.
If you do not have T1 weighted images, you can still process your diffusion data through BDP. http://brainsuite.org/processing/diffusion/
make sure to use the flag –no-structural-registration
quick question, are you running the cortical surface extraction sequence on T1 or diffusion images?
The surfaces we generate do not include subcortical nor extratentorial structures.
You can generate surfaces from any mask or label.
If you have the svreg.label.nii.gz file loaded, open up the tools–> mask tool–> label mask tool
then click “update list”
you can then select any ROI (subcortical structures are in the 600s) and then click “make surfaces for each label”
These surfaces can be saved using the surface display toolbox (hit “s” and it will appear or Surface->Show Surface Display Properties Toolbox)
Your question on saving views was answered here: http://forums.brainsuite.org/forums/topic/bci-dni_brain_atlas-how2-save-retrieve-different-views/
you can remove the slices from the surface viewer by hitting ctrl+v or cmd+v
you can also unclick “slow slices” option in the surface display toolbox. Specific orientations can also optionally be turned off.
You can view your surface as a solid color by going to the surface display toolbox.
select your surface then select “solid color”
unclick that and your colorized surfaces will be reappear
Good luck. Glad you’re enjoying our interfaceJune 9, 2018 at 4:47 am in reply to: BCI-DNI_brain_atlas: how2 Save & Retrieve different views #1290
you can create a .bst file that you can drag and drop onto brainsuite and will load a specified set of files.
instructions found here: http://brainsuite.org/formats/formatsbst/
you can try cutting through the surfaces by pressing keys “x” “y” or “z” on the surface viewer.
x : sagittal
y : coronal
z : axial
The surface will cut through where ever your crosshairs are located on the volume slices.
Hi Dan, our atlases will be found with your installation files. for example
you will see a directory for the BCI-DNI_brain atlas and BrainSuiteAtlas1. I recommend the BCI-DNI_brain atlas.
drag and drop files ending in:
.bfc.nii.gz (or BCI-DNI_brain.nii.gz for inclusion of skull and scalp)
.all.dfc (right and left will only load one at a time)
and under File–>open–>label volume
select the “BCI-DNI_brain.label.nii.gz” file
To give you a few tips:
you can learn about navigation controls here: http://brainsuite.org/interface/
you can click anywhere on the volume slices or double click anywhere on the surface and the name of the region will appear on the bottom of the interface. There’s also some fun things you can do for visualization by opening up the mask toolbox.
You can see the names and description of the sulcal curves (.dfc files) by opening up the sulcal toolbox
click around, experiment and have fun. Let us know if you have any other questions.