Dear AFNI experts,
I am interested in extracting cerebellum segmentation mask from SUIT cerebellum probabilistic mask (attached) and use that segmentation for the seed for resting-state analysis. Could you please let me know if there is any way to extract the each component mask?
You have already downloaded the atlas dataset from our website, so first change to that directory
cd dir_cerebellum # use the directory where you put it
set AFNI environment variable to use the new atlases in this directory
@AfniEnv -set AFNI_SUPP_ATLAS_DIR
check if the SUIT cerebellum atlases are recognized by AFNI
see the list of atlas structures in the header of one of the atlases
3dinfo -atlas_points Cerebellum-SUIT.nii.gz
extract one of the regions from that atlas - using 3dcalc or any AFNI C program
3dcalc -a “Cerebellum-SUIT::Left_Fastigial” -expr a -prefix leftfast.nii.gz
another way to extract a region - using whereami
whereami -prefix rightfast.nii.gz -mask_atlas_region “Cerebellum-SUIT::Right_Fastigial”
resample to EPI grid (grid of some dataset in MNI space) starting with the atlas again
3dresample -master ~/AFNI_data6/afni/epi_r1_MNI+tlrc. -inset “Cerebellum-SUIT::Right_Fastigial” -prefix right_fast_rs.nii.gz
Thank you so much for the instruction. Could you please clarify one thing? I am a little bit confused by the last step (resample to EPI grid (grid of some dataset in MNI space) starting with the atlas again) for the two reasons.
First, I could not find epi_r1_MNI+tlrc in the directory you suggested. I could only find epi_r1+orig. Did I make a mistake when installing AFNI or can I just simply convert the orig to tlrc?
Second, regarding the 3dresample, I don’t need to 3dresample the extracted mask to errts.fanaticor in the proc results data of the participants? Can I just simply use the extracted mask as a seed for the connectivity analysis?
Thank you in advance for your help!
Those are just examples of different ways to use masks. If you have your own EPI dataset, you can use a command like that one to resample the mask to your EPI dataset that is in the same space as the atlas.
Thanks for the clarification! That really helps.