August 1, 2018 at 3:55 pm #1400
I am using your brainsuite software to process DTI images with the goal of creating connectivity graphs. I keep running into the issue, independent of which subject’s brain image I use, where the cerebrum labeling works improperly and selects a much smaller portion of the brain than it should. I have looked at the cerebrum labeling website (http://brainsuite.org/processing/surfaceextraction/cerebrum/) and tweaked values based on that with little success. Do you have any advice on how to get brainsuite to recognize the image better?
Here is a link to image of the problem:
Thanks in advance
August 1, 2018 at 6:09 pm #1401
quick question, are you running the cortical surface extraction sequence on T1 or diffusion images?
August 1, 2018 at 6:35 pm #1402
August 1, 2018 at 6:40 pm #1403
August 2, 2018 at 2:35 pm #1404
Oh ok, I had not noticed that flag, thank you.
Is it possible to create a connectivity graph using diffusion images? It seems that to run SVreg, which seems to be required for the connectivity graph because the program needs the SVreg ROI label, you must first run the cortical extraction sequence. Is there a way to run SVreg without first running CSE? Or alternatively is there a way to create the connectivity graph without running SVreg?
What would the order of steps I would take to do so if either of the above are possible?
Many thanks, sorry for all the questions.
August 8, 2018 at 2:06 pm #1420
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.
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