Mri binarize: Difference between revisions
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* '''This approach has been abandoned -- Check [http://ccnlab.psy.buffalo.edu/wiki/index.php/Working_with_ROIs_(Freesurfer) this] out instead.''' | |||
At this point you should have conducted group stats (mri_glmfit) and pulled out whatever ROI's of interest. Now you'll convert your group average .annot label file | If you have data from different time points, as with the booth data, and want to make comparisons of ROI's across time points you'll want to be looking at the same voxels. Here's how to do that with freesurfer. | ||
At this point you should have conducted group stats (mri_glmfit) and pulled out whatever ROI's are of interest. Now you'll need to convert your group average .annot label file | |||
to a volume, so that we can use the binarize function. | to a volume, so that we can use the binarize function. | ||
For T1 & T2 | For T1 & T2 | ||
mri_label2vol --annot | mri_label2vol --annot rh.T1_200functional_subclusters.annot --temp T1.mgz --o rh.T1_200funclust.mgz --subject fsaverage --hemi rh --reg reg.mni152.2mm.dat | ||
mri_label2vol --annot | mri_label2vol --annot lh.T1_200functional_subclusters.annot --temp T1.mgz --o lh.T1_200funclust.mgz --subject fsaverage --hemi lh --reg reg.mni152.2mm.dat | ||
mri_label2vol --annot | mri_label2vol --annot rh.T2_200functional_subclusters.annot --temp T1.mgz --o rh.T2_200funclust.mgz --subject fsaverage --hemi rh --reg reg.mni152.2mm.dat | ||
mri_label2vol --annot | mri_label2vol --annot lh.T2_200functional_subclusters.annot --temp T1.mgz --o lh.T2_200funclust.mgz --subject fsaverage --hemi lh --reg reg.mni152.2mm.dat | ||
Questions: Use fsaverage's T1.mgz as a template, vs the orig.mgz, and from /mri or /mri.2mm? Registery reg.mni152.2mm.dat vs. reg.2mm.mni152.dat ?? | |||
Now that you have volumes, | Now that you have volumes, use the mri_binarize function to set voxels of min values (0.1 seems to grab all voxels) to 1 for T1 and 2 for T2 (specified by binval). | ||
For Left and Right Hemi | For Left and Right Hemi | ||
mri_binarize | mri_binarize --i lh.T1_200funclust.mgz --min 0.1 --binval 1 --o lh.T1_bin.mgz | ||
mri_binarize | mri_binarize --i lh.T2_200funclust.mgz --min 0.1 --binval 2 --o lh.T2_bin.mgz | ||
mri_binarize --i rh.T1_200funclust.mgz --min 0.1 --binval 1 --o rh.T1_bin.mgz | |||
mri_binarize --i rh.T2_200funclust.mgz --min 0.1 --binval 2 --o rh.T2_bin.mgz | |||
Use fscalc to add T1 and T2 for left and right hemi's. This will cause voxels only in T1 to be one, only in T2 to | |||
be 2, and voxels in both to be 3. | |||
fscalc lh.T1_bin.mgz add lh.T2_bin.mgz --o lh.T1andT2.mgz | |||
fscalc rh.T1_bin.mgz add rh.T2_bin.mgz --o rh.T1andT2.mgz | |||
The venn diagram is cool, but for the analysis you want the voxels that are coded as 3. When converting the volume | |||
back to a label file, use mri_cor2label and specify labelid as 3. | |||
mri_cor2label | mri_cor2label | ||
--i lh.T1andT2.mgz | |||
--id 3 | |||
--l lh.T1_T2_200subclust.annot | |||
--surf fsaverage lh | |||
mri_cor2label | mri_cor2label | ||
--i rh.T1andT2.mgz | |||
--id 3 | |||
--l rh.T1_T2_200subclust.annot | |||
--surf fsaverage rh | |||
This also has options for writing label volume in file and interpreting input volume as surface overlay, which may be more appropriate? | |||
And, finally apply the new annot file to each subject, for Left and Right Hemi | Now you can check the .annot files by importing them in tksurfer with fsaverage. -- Error, vertex index out of range, leading me to believe there is an error with the reg file I picked, or that I should use the surface overlay option in mri_cor2label.. More on this later. | ||
And, finally apply the new annot file to each subject, for Left and Right Hemi (to run this template as is, you'll have to move the new .annot files into the fsaverage label folder) | |||
mri_surf2surf \ | mri_surf2surf \ | ||
--srcsubject fsaverage \ | --srcsubject fsaverage \ | ||
--trgsubject FS_T1_501 \ | --trgsubject FS_T1_501 \ | ||
--hemi lh \ | --hemi lh \ | ||
--sval-annot $SUBJECTS_DIR/fsaverage/label/lh. | --sval-annot $SUBJECTS_DIR/fsaverage/label/lh.T1_T2_200subclust.annot \ | ||
--tval $SUBJECTS_DIR/FS_T1_501/label/lh. | --tval $SUBJECTS_DIR/FS_T1_501/label/lh.T1_T2_200subclust.annot | ||
mri_surf2surf \ | |||
--srcsubject fsaverage \ | |||
--trgsubject FS_T1_501 \ | |||
--hemi rh \ | |||
--sval-annot $SUBJECTS_DIR/fsaverage/label/rh.T1_T2_200subclust.annot \ | |||
--tval $SUBJECTS_DIR/FS_T1_501/label/rh.T1_T2_200subclust.annot | |||
Latest revision as of 15:13, 13 July 2017
- This approach has been abandoned -- Check this out instead.
If you have data from different time points, as with the booth data, and want to make comparisons of ROI's across time points you'll want to be looking at the same voxels. Here's how to do that with freesurfer.
At this point you should have conducted group stats (mri_glmfit) and pulled out whatever ROI's are of interest. Now you'll need to convert your group average .annot label file to a volume, so that we can use the binarize function.
For T1 & T2
mri_label2vol --annot rh.T1_200functional_subclusters.annot --temp T1.mgz --o rh.T1_200funclust.mgz --subject fsaverage --hemi rh --reg reg.mni152.2mm.dat mri_label2vol --annot lh.T1_200functional_subclusters.annot --temp T1.mgz --o lh.T1_200funclust.mgz --subject fsaverage --hemi lh --reg reg.mni152.2mm.dat
mri_label2vol --annot rh.T2_200functional_subclusters.annot --temp T1.mgz --o rh.T2_200funclust.mgz --subject fsaverage --hemi rh --reg reg.mni152.2mm.dat mri_label2vol --annot lh.T2_200functional_subclusters.annot --temp T1.mgz --o lh.T2_200funclust.mgz --subject fsaverage --hemi lh --reg reg.mni152.2mm.dat
Questions: Use fsaverage's T1.mgz as a template, vs the orig.mgz, and from /mri or /mri.2mm? Registery reg.mni152.2mm.dat vs. reg.2mm.mni152.dat ??
Now that you have volumes, use the mri_binarize function to set voxels of min values (0.1 seems to grab all voxels) to 1 for T1 and 2 for T2 (specified by binval).
For Left and Right Hemi
mri_binarize --i lh.T1_200funclust.mgz --min 0.1 --binval 1 --o lh.T1_bin.mgz mri_binarize --i lh.T2_200funclust.mgz --min 0.1 --binval 2 --o lh.T2_bin.mgz
mri_binarize --i rh.T1_200funclust.mgz --min 0.1 --binval 1 --o rh.T1_bin.mgz mri_binarize --i rh.T2_200funclust.mgz --min 0.1 --binval 2 --o rh.T2_bin.mgz
Use fscalc to add T1 and T2 for left and right hemi's. This will cause voxels only in T1 to be one, only in T2 to
be 2, and voxels in both to be 3.
fscalc lh.T1_bin.mgz add lh.T2_bin.mgz --o lh.T1andT2.mgz fscalc rh.T1_bin.mgz add rh.T2_bin.mgz --o rh.T1andT2.mgz
The venn diagram is cool, but for the analysis you want the voxels that are coded as 3. When converting the volume back to a label file, use mri_cor2label and specify labelid as 3.
mri_cor2label --i lh.T1andT2.mgz --id 3 --l lh.T1_T2_200subclust.annot --surf fsaverage lh
mri_cor2label --i rh.T1andT2.mgz --id 3 --l rh.T1_T2_200subclust.annot --surf fsaverage rh
This also has options for writing label volume in file and interpreting input volume as surface overlay, which may be more appropriate?
Now you can check the .annot files by importing them in tksurfer with fsaverage. -- Error, vertex index out of range, leading me to believe there is an error with the reg file I picked, or that I should use the surface overlay option in mri_cor2label.. More on this later.
And, finally apply the new annot file to each subject, for Left and Right Hemi (to run this template as is, you'll have to move the new .annot files into the fsaverage label folder)
mri_surf2surf \ --srcsubject fsaverage \ --trgsubject FS_T1_501 \ --hemi lh \ --sval-annot $SUBJECTS_DIR/fsaverage/label/lh.T1_T2_200subclust.annot \ --tval $SUBJECTS_DIR/FS_T1_501/label/lh.T1_T2_200subclust.annot
mri_surf2surf \ --srcsubject fsaverage \ --trgsubject FS_T1_501 \ --hemi rh \ --sval-annot $SUBJECTS_DIR/fsaverage/label/rh.T1_T2_200subclust.annot \ --tval $SUBJECTS_DIR/FS_T1_501/label/rh.T1_T2_200subclust.annot