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| This page will outline how to split a full FreeSurfer parcelation into multiple seeds To use a portion of the full Freesurfer parcellation ("split parcellation"), follow the [[FsFastFunctionalConnectivityWalkthrough |additional steps here]] - and resume with step 5 on this page... | This page will outline how to split a full FreeSurfer aparc annotation into multiple seeds to use a portion of the full Freesurfer parcellation ("split parcellation") as your seed region. *STEP 1: create a text file with the name of the full parcellation of interest and the number of seeds. Possible structures can be found here: $FREESURFER_HOME/average/colortable_desikan_killiany.txt NOTE: The method I've show below divides the parcellation, orthogonally along its long axis. There is also a method of using mris_divide_parcellation that specifies a unit of area for each seed. *STEP 2: use [[mris_divide_parcellation]]. This command will generate a new parcellation including your split ROI, as well as all original parcellations outside your chosen region. set splitN = 3 <-this is the number of divisions to make. echo "isthmuscingulate 3" > seed.isthmuscingulate.3.txt . set splitstem = <hemi>.isthmuscingulate.3.split <-name for divided surface annotation. |
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| *STEP 4: Use fcseed-config to record the parameters you wish to pass to your connectivity analysis. | mris_divide_parcellation <recondir> <hemi> aparc.annot seed.isthmuscingulate.3.txt ${hemi}.${splitN}split |
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| Sample command: fcseed-config -segid 1010 -fcname mean.L_Posteriorcingulate.dat -fsd bold -mean -cfg mean.L_Posteriorcingulate.config |
*STEP 3: use [[mri_annotation2label]] to create labels from the new annotation. This will create a label for each parcellation (including labels for regions outside of your desired seed region). The labels will be deposited in the subject's recondir/label directory. |
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| This example will use the FreeSurfer cortical segmentation for the left posterior cingulate (segID: 1010). For seed regions, we recommend generating the mean signal timecourse by using "-mean" | mri_annotation2label --subject <recondir> \ --hemi <hemi> \ |
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| --labelbase <hemi>.isthmuscingulate.3 \ | |
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| --annotation 3split \ | |
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| --surface pial To remove the excess labels, I've used this method: @ splitN2 = $splitN + 1 <-this number will be helpful when removing excess labels set rmextra = `find $SUBJECTS_DIR/<recondir>/label -maxdepth 1 -type f | \ grep <hemi>.isthmuscingulate.3 | \ sort -nr | \ sed -n ${splitN2},500p` <-this command lists all files in the label dir, greps for our label name, <-sorts numerically in reverse, then grabs all labels after the first 3 echo " REMOVING excess labels " rm -v $rmextra set lbls = `find $ldir -maxdepth 1 -type f | grep <hemi>.isthmuscingulate.3 | sort -nr` <-grabs our seed labels *STEP 4: check that you've grabbed the correct seed labels by loading them in [[tksurfer]] *STEP 5: Use [[mri_label2vol]] on each of the split seed labels to obtain a segmentation volume for each. mri_label2vol --label <label> \ --temp $SUBJECTS_DIR/<recondir>/mri/brainmask.nii.gz \ --proj frac 0 1 .1 \ --subject <recondir> --hemi <hemi> \ --regheader $SUBJECTS_DIR/<recondir>/mri/brainmask.nii.gz \ --o <outsegname> *STEP 6: Use fcseed-config to record the parameters you wish to pass to your connectivity analysis. Sample command for running the mean time course and using the first (1) of the 3 seed split: set type = mean <- For seed regions, we recommend generating the mean signal timecourse by using "-mean" set segname = <hemi>.isthmuscingulate.split3.1 fcseed-sess -s <subject> \ -segid 1 \ -o ${type}.${segname}.dat \ -seg <outsegname> \ -fsd bold \ -${type} \ -cfg {type}.${segname}.config |
Note: this is a companion page to the FsFastFunctionalConnectivityWalkthrough page.
This page will outline how to split a full FreeSurfer aparc annotation into multiple seeds to use a portion of the full Freesurfer parcellation ("split parcellation") as your seed region.
*STEP 1: create a text file with the name of the full parcellation of interest and the number of seeds. Possible structures can be found here: $FREESURFER_HOME/average/colortable_desikan_killiany.txt
- NOTE: The method I've show below divides the parcellation, orthogonally along its long axis.
- There is also a method of using mris_divide_parcellation that specifies a unit of area for each seed.
*STEP 2: use mris_divide_parcellation. This command will generate a new parcellation including your split ROI, as well as all original parcellations outside your chosen region.
set splitN = 3 <-this is the number of divisions to make. echo "isthmuscingulate 3" > seed.isthmuscingulate.3.txt . set splitstem = <hemi>.isthmuscingulate.3.split <-name for divided surface annotation.
mris_divide_parcellation <recondir> <hemi> aparc.annot seed.isthmuscingulate.3.txt ${hemi}.${splitN}split
*STEP 3: use mri_annotation2label to create labels from the new annotation. This will create a label for each parcellation (including labels for regions outside of your desired seed region). The labels will be deposited in the subject's recondir/label directory.
mri_annotation2label --subject <recondir> \
--hemi <hemi> \
--labelbase <hemi>.isthmuscingulate.3 \ --annotation 3split \ --surface pial
To remove the excess labels, I've used this method:
@ splitN2 = $splitN + 1 <-this number will be helpful when removing excess labels
set rmextra = `find $SUBJECTS_DIR/<recondir>/label -maxdepth 1 -type f | \
grep <hemi>.isthmuscingulate.3 | \
- sort -nr | \
- sed -n ${splitN2},500p`
<-this command lists all files in the label dir, greps for our label name, <-sorts numerically in reverse, then grabs all labels after the first 3
echo " REMOVING excess labels " rm -v $rmextra set lbls = find $ldir -maxdepth 1 -type f | grep <hemi>.isthmuscingulate.3 | sort -nr <-grabs our seed labels
*STEP 4: check that you've grabbed the correct seed labels by loading them in tksurfer
*STEP 5: Use mri_label2vol on each of the split seed labels to obtain a segmentation volume for each.
mri_label2vol --label <label> \
--temp $SUBJECTS_DIR/<recondir>/mri/brainmask.nii.gz \ --proj frac 0 1 .1 \ --subject <recondir> --hemi <hemi> \ --regheader $SUBJECTS_DIR/<recondir>/mri/brainmask.nii.gz \ --o <outsegname>
*STEP 6: Use fcseed-config to record the parameters you wish to pass to your connectivity analysis.
Sample command for running the mean time course and using the first (1) of the 3 seed split:
set type = mean <- For seed regions, we recommend generating the mean signal timecourse by using "-mean" set segname = <hemi>.isthmuscingulate.split3.1 fcseed-sess -s <subject> \
- -segid 1 \ -o ${type}.${segname}.dat \
-seg <outsegname> \ -fsd bold \ -${type} \ -cfg {type}.${segname}.config
- -segid 1 \ -o ${type}.${segname}.dat \
Now resume with step 5 on this page...
