141 lines
5.2 KiB
Plaintext
141 lines
5.2 KiB
Plaintext
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fsaverage/mri.2mm
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These are volumes sampled into a 2mm space. The primary purpose of
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these is to support volume-based fMRI analysis as performed in
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FS-FAST. This 2mm space is the space that is used by default in
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FS-FAST to perform "talairach" group analysis (ie, in the mni305
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space). The raw functional data are sampled into this space when
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preproc-sess is run with the -mni305 flag. When a group analysis is
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done, the output space will be this 2mm space. It is possible to use a
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1mm space, but this can create huge files.
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These files can be used to render the statistical results on a volume
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(though this is not really necessary as they can be rendered directly
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on the 1mm volumes). Also, the aseg.mgz created can be used to
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generate labels/masks of subcortical structures directly in the group
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average space. These can be used with mri_volcluster.
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These files were created with the following commands:
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# Resample each of these volumes using trilin
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foreach vol (orig brain brainmask mni305.cor T1)
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mri_vol2vol --mov ../mri/$vol.mgz --s fsaverage --tal \
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--o $vol.mgz --no-save-reg
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end
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# Resample the aseg
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mri_label2vol --seg ../mri/aseg.mgz --temp orig.mgz \
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--regheader ../mri/orig.mgz --o aseg.mgz
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Note: we don't want to do aparc+aseg because the surface-based
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labels should really be used in a surface-based analysis.
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# checks
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tkmedit -f T1.mgz -aux brain.mgz -seg ./aseg.mgz
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tkregister2 --mov ./orig.mgz --s fsaverage --regheader --reg junk
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#-----------------------------------------------------------
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Creation of subcortical mask. A challenge for doing analyses in three
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ROIs (left hemi, righ hemi, subcortical) is making the ROIs mutally
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exclusive while not excluding any voxels. This is particularly hard in
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this analysis because a cortical voxel in one subject can map to a
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subcortical voxel in another when using the transform to MNI305
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space.
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A map of the subcortical structures for each of the buckner 40 where
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mapped into the mni305 2mm space. A probability map was then
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created. This was repeated for the cortical ribbon and for cerebellum
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by itself.
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1. An initial mask was created taking voxels with any
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subcortical origins in the native space as long as they had fewer than
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80% cortex.
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2. Cerebellum is a special case because it is so close to fusiform
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that it is easy to get bleed over. For this case, a mask was made of
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any cerebellum voxels that had at least 20% cortex. Any voxels in this
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mask were then excluded from the mask from step 1 to create a new
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mask.
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3. Little islands were excluded by running connected components and
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taking the largest cluster.
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4. This mask was then dialted by one voxel then eroded by one voxel to
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remove holes and make the final mask less jagged.
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# ----- Below For Version 5 --------------------#
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Everything above is for 5.1 and higher.
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The mask is created based on mri/subcort.prob.mgz which was created
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with make_average_subcort. subcort.prob.mgz is the raw probability of
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a voxel being in a subcortical gray matter structure based on the
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Buckner40. Inevitably, this mask will include more than just
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subcortial gray matter structures, but we would rather have the mask
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be too big than too small.
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# Resample into 2mm space
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mri_vol2vol --mov ../mri/subcort.prob.mgz \
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--s fsaverage --tal --o subcort.prob.mgz \
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--no-save-reg
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Threshold at .05 (meaning that at least 5% of the subjects at
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a voxel must have a subcortical label). Also dilate by 2 to
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expand the mask.
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mri_binarize --i subcort.prob.mgz --min .05 \
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--dilate 2 --o subcort.mask2.mgz
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Erode by 1. The net result of dilating by 2 then eroding
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by 1 is that holes are filled in and the edges are
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a little smoother.
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mri_binarize --i subcort.mask2.mgz --min .5 \
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--erode 1 --o subcort.mask.mgz
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rm subcort.mask2.mgz
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#-----------------------------------------------------------
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Creation of registration matrix between the 2mm fsaverage/mni305 space
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and the 2mm mni152 space. This can be used to convert data in the 2mm
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fsaverage/mni305 space into the mni152 2mm space.
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set d = $SUBJECTS_DIR/fsaverage
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# Create registration matrix between the full 256^3, 1mm3
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# volume and the 2mm space (simple regheader)
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tkregister2 --mov $d/mri.2mm/brain.mgz --targ $d/mri/brain.mgz \
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--regheader --reg $d/mri.2mm/reg.2mm.dat --noedit
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# Registration between the fsaverage/mni305 subject (full 256^3, 1mm3)
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# and the 2mm mni152 space. This was created by hand.
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# $FREESURFER_HOME/average/mni152.register.dat
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# Compute the registration between the 2mm fsaverage space and the
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# mni152 2mm space by concatenating the two matrices above.
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mri_matrix_multiply -im $d/mri.2mm/reg.2mm.dat \
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-iim $FREESURFER_HOME/average/mni152.register.dat \
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-om $d/mri.2mm/reg.2mm.mni152.dat
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# Check the registration
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tkregister2 --mov $d/mri.2mm/brain.mgz \
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--targ $FSLDIR/data/standard/MNI152_T1_2mm.nii.gz \
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--reg $d/mri.2mm/reg.2mm.mni152.dat
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# To view without reslicing
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tkmedit -f $FSLDIR/data/standard/MNI152_T1_2mm.nii.gz \
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-overlay sig.nii -reg reg.2mm.mni152.dat
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# To do the conversion/reslicing, run something like
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mri_vol2vol --mov sig.nii --reg reg.2mm.mni152.dat \
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--targ $FSLDIR/data/standard/MNI152_T1_2mm.nii.gz \
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--o sig.mni152.nii
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# To view with reslicing
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tkmedit -f $FSLDIR/data/standard/MNI152_T1_2mm.nii.gz \
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-overlay sig.mni152.nii
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