help > comparison figure from cordinates
Showing 1-5 of 5 posts
Display:
Results per page:
Jun 12, 2023  04:06 PM | shirgalin
comparison figure from cordinates

hi,


I'm trying to compare different brain areas in mode A versus mode B using  X, Y, Z coordinates and Z values provided in various research articles. Specifically, I would like to create a diagram with two layers: one representing brain areas associated with depression and another layer to compare and identify similarities between depression and cardiac activation.


I've gone through the manual, but I'm still unsure about the process of creating this diagram. I was wondering if someone understands how to achieve this using MRIcron. Any guidance, specific steps, or tips would be greatly appreciated

Jun 13, 2023  06:06 PM | Chris Rorden
RE: comparison figure from cordinates

You will want to save your contrast image in NIfTI format, and then you can load the image just like a statistical map. For example here


http://brainmap.org/software.html#Sleuth


 


Once you create the NIfTI image "MyMap.nii" you could visualize it, for example the MRIcroGL script:


 


import gl
gl.resetdefaults()
gl.loadimage('spm152')
gl.overlayload('myMap')

Jun 14, 2023  08:06 AM | shirgalin
RE: comparison figure from cordinates

thank you!!


 


 

Jun 18, 2023  01:06 PM | shirgalin
RE: comparison figure from cordinates

I am trying to create 2 different VOIs in different colors overlaid on TLRC tamplate (see attached template file). I'm able to create different VOIs and see them on the template, but not with different colors. also, it looks like only 2 points can be seen on a single VOI each time. Saving they seperately as NIfTI files and trying to open them doesn't work either. (dissapear/change color).


 


do you know this problen and how to fix it?


 


thank you!

Jun 18, 2023  01:06 PM | Chris Rorden
RE: comparison figure from cordinates

You can use MRIcroGL's Draw/DrawColor menu items to choose multiple colors:


  https://www.nitrc.org/plugins/mwiki/inde...


alternatively, you can use NiiVue


  https://niivue.github.io/niivue/features...