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To load an existing label, for example lh.cortex.label, run ---- {{{ less 004/label/lh.cortex.label |
To load an existing label, for example lh.BA45.label, run ---- {{{ less 004/label/lh.BA45.label |
Anatomical ROI analysis
This tutorial gives a brief introduction to anatomical ROI analysis which includes working with label files, extracting ROI measures from the anatomical data, group statistics etc. Make sure you have set your SUBJECTS_DIR to correct location.
Relationship between segmentation, parcellation and LookUp Table (LUT)
Open the subject in tkmedit using the following command
tkmedit 004 orig.mgz -aux aparc+aseg.mgz \ -seg aparc+aseg.mgz $FREESURFER_HOME/FreeSurferColorLUT.txt
Open another terminal to load the subject in tksurfer, using the following command.
tksurfer 004 lh inflated -annot aparc.annot
Run the following command to display the contents of LUT
less $FREESURFER_HOME/FreeSurferColorLUT.txt
Click on a point on the image loaded in tkmedit. You can see the structure name in the tkmedit toolbar. Look at the Aux value, find value in LUT, which you have opened using the command mentioned above. See that it is the same structure as listedin tkmedit.
Click on a point in tksurfer and see structure name. Note that the name does not have lh or rh in it. Click on the Save Point tool button 
, and then click on Goto Point tool button 
on the tkmedit toolbar. You will notice that the structure name in tkmedit has lh or rh in it.
Label files
This section gives the details of commands to load an existing label file in text editor, tkmedit, and tksurfer.
To load an existing label, for example lh.BA45.label, run
less 004/label/lh.BA45.label
To load a label in tkmedit, first load the subject you want to work on, in tkmedit.
tkmedit 004 orig.mgz
Then on the tkmedit toolbar, go to File-> Label --> Load Label --> lh.BA45.label
To load the label in tksurfer, make sure you load the subject in tksurfer.
tksurfer 004 lh inflated
On the tksurfer toolbar, go to File --> Label --> Load Label --> lh.BA45.label You can also load the label from the tksurfer tool bar using Ctrl - right mouse button on the 'Show labels' tool button 
. Browse the label you want to load and click 'OK'
Individual Stats files
During the normal FreeSurfer processing stream, via the recon-all script, (a freesurfer tutorial is available.) some statistical output files are generated. They are kept in each subjects stats/ subdirectory, and are a result of the subcortical segmentation, aseg, and the cortical parcellation, aparc. These tables include information on each labeled region for the individual subject.
cd $SUBJECTS_DIR/004/stats less aseg.stats
Details are as follows when you run the command line above.
aseg.stats
The statistical output from the subcortical segmentation, called aseg.stats, is a regular text file and will contain the volumes of specific structures. For example, you can obtain information such as the volume of left hippocampus and it's mean intensity from this file.
At the head of the text file there will be information about the command that was run, the version used, the user who ran it and a time stamp. Following this there is information about the volume of the entire brain:
# Title Segmentation Statistics # # generating_program mri_segstats # cvs_version $Id: mri_segstats.c,v 1.11.2.5 2006/04/13 18:57:07 nicks Exp $ # cmdline mri_segstats --seg mri/aseg.mgz --sum stats/aseg.stats --pv mri/norm.mgz --ctab-default --excludeid 0 --brain-vol-from-seg --brainmask mri/brainmask.mgz --in mri/norm.mgz --in-intensity-name norm --in-intensity-units MR --etiv --subject 004 # sysname Linux # hostname node0350 # machine x86_64 # user FS-user # anatomy_type volume # # SUBJECTS_DIR /buckner_data/group_study # subjectname 004 # BrainMaskFile mri/brainmask.mgz # BrainMaskFileTimeStamp 2006/24/03 13:47:46 # Measure BrainMask, BrainMaskNVox, Number of Brain Mask Voxels, 1744896, unitless # Measure BrainMask, BrainMaskVol, Brain Mask Volume, 1744896.000000, mm^3 # Measure BrainSeg, BrainSegNVox, Number of Brain Segmentation Voxels, 1255291, unitless # Measure BrainSeg, BrainSegVol, Brain Segmentation Volume, 1255291.000000, mm^3# Measure IntraCranialVol, ICV, Intracranial Volume, 1679242.759627, mm^3 # SegVolFile mri/aseg.mgz # SegVolFileTimeStamp 2006/24/03 21:52:14 # ColorTable /space/freesurfer/centos4.0_x86_64/stable/FreeSurferColorLUT.txt # ColorTableTimeStamp 2006/22/03 05:48:11 # InVolFile mri/norm.mgz # InVolFileTimeStamp 2006/24/03 13:55:16 # InVolFrame 0 # PVVolFile mri/norm.mgz # PVVolFileTimeStamp 2006/24/03 13:55:16 # ExcludeSegId 0 # VoxelVolume_mm3 1
This shows the number of voxels in the brainmask (BrainMaskNVox), the volume of the brainmask (BrainMaskVol), the number of voxels in the brainseg (BrainSegNVox), the volume of the brainseg (BrainSegVol), and the intracranial volume (ICV). This part of the file also tells us that the brainmask.mgz volume is being used as BrainMask (BrainMaskFile mri/brainmask.mgz) and the aseg.mgz segmentation is being used as the SegVol (SegVolFile mri/aseg.mgz). The number of voxels and the volumes should be the same for this subject, since this part of the file also tells us that the voxel volume is 1 mm3 (VoxelVolume_mm3 1) - and volume is measured in mm3.
The next section of this file defines the column headers, field name, and units for the rest of the table:
# TableCol 1 ColHeader Index # TableCol 1 FieldName Index # TableCol 1 Units NA # TableCol 2 ColHeader SegId # TableCol 2 FieldName Segmentation Id # TableCol 2 Units NA # TableCol 3 ColHeader NVoxels # TableCol 3 FieldName Number of Voxels # TableCol 3 Units unitless # TableCol 4 ColHeader Volume_mm3 # TableCol 4 FieldName Volume # TableCol 4 Units mm^3 # TableCol 5 ColHeader StructName # TableCol 5 FieldName Structure Name # TableCol 5 Units NA # TableCol 6 ColHeader normMean # TableCol 6 FieldName Intensity normMean # TableCol 6 Units MR # TableCol 7 ColHeader normStdDev # TableCol 7 FieldName Itensity normStdDev # TableCol 7 Units MR # TableCol 8 ColHeader normMin # TableCol 8 FieldName Intensity normMin # TableCol 8 Units MR # TableCol 9 ColHeader normMax # TableCol 9 FieldName Intensity normMax # TableCol 9 Units MR # TableCol 10 ColHeader normRange # TableCol 10 FieldName Intensity normRange # TableCol 10 Units MR # NRows 403 # NTableCols 10
We can expect to see the Segmentation Id, Number of Voxels, Volume, Structure Name, Intensity normMean, Itensity normStdDev, Intensity normMin, Intensity normMax, and Intensity normRange for each entry in the table.
The remainder of the table shows this information for all the structures that are labeled in the aseg:
# ColHeaders Index SegId NVoxels Volume_mm3 StructName normMean normStdDev normMin normMax normRange 2 2 237201 237201.0 Left-Cerebral-White-Matter 107.5612 11.3261 31.0000 188.0000 157.0000 3 3 249096 249096.0 Left-Cerebral-Cortex 69.8956 11.0623 0.0000 139.0000 139.0000 4 4 31329 31329.0 Left-Lateral-Ventricle 23.0385 11.1648 7.0000 91.0000 84.0000 5 5 1735 1735.0 Left-Inf-Lat-Vent 42.2160 15.5492 14.0000 94.0000 80.0000 7 7 13767 13767.0 Left-Cerebellum-White-Matter 87.6124 7.8224 43.0000 116.0000 73.0000 8 8 48245 48245.0 Left-Cerebellum-Cortex 60.1777 9.4993 25.0000 94.0000 69.0000 10 10 7025 7025.0 Left-Thalamus-Proper 89.5336 11.9082 19.0000 126.0000 107.0000 11 11 5252 5252.0 Left-Caudate 77.3650 11.3959 45.0000 105.0000 60.0000 12 12 7993 7993.0 Left-Putamen 81.3400 9.7069 28.0000 115.0000 87.0000 13 13 2144 2144.0 Left-Pallidum 97.6942 11.7513 36.0000 121.0000 85.0000 . . . .
aparc.stats
The statistical output from the cortical parcellation, called lh.aparc.stats and rh.aparc.stats, is a regular text file and will contain the thickness of specific structures. For example, you can obtain information such as, how big is left superior temporal gyrus and it's average thickness from this file.
cd $SUBJECTS_DIR/004/stats less lh.aparc.stats
At the head of the text file there will be information about the command that was run, the version used, the user who ran it and a time stamp. Following this there is information about the volume of the entire brain:
# Table of FreeSurfer cortical parcellation anatomical statistics # # CreationTime 2006/04/25-09:31:20-GMT # generating_program mris_anatomical_stats # cvs_version $Id: mris_anatomical_stats.c,v 1.35.2.1 2006/04/21 19:45:19 nicks Exp $ # mrisurf.c-cvs_version $Id: mrisurf.c,v 1.441.2.3 2006/04/12 02:03:02 nicks Exp $ # cmdline mris_anatomical_stats -mgz -f ../stats/lh.aparc.stats -b -a ../label/l h.aparc.annot -c ../stats/aparc.annot.ctab 004 lh # sysname Linux # hostname node0350 # machine x86_64 # user FS-user # # SUBJECTS_DIR /buckner_data/group_study # anatomy_type surface # subjectname 004 # hemi lh # AnnotationFile ../label/lh.aparc.annot # AnnotationFileTimeStamp 2006/25/03 05:31:10 # TotalWhiteMatterVolume 634178 mm^3 # Measure Cortex, NumVert, Number of Vertices, 150889, unitless # Measure Cortex, SurfArea, Surface Area, 102409, mm^2
This shows the total white matter volume (TotalWhiteMatterVolume), the number of vertices in the cortex (NumVert), and the surface area of the cortex (SurfArea). This part of the file also tells us that the lh.aparc.annot is being used as the annotation file (AnnotationFile ../label/lh.aparc.annot).
The next section of this file defines the column headers, field name, and units for the rest of the table:
# NTableCols 10 # TableCol 1 ColHeader StructName # TableCol 1 FieldName Structure Name # TableCol 1 Units NA # TableCol 2 ColHeader NumVert # TableCol 2 FieldName Number of Vertices # TableCol 2 Units unitless # TableCol 3 ColHeader SurfArea # TableCol 3 FieldName Surface Area # TableCol 3 Units mm^2 # TableCol 4 ColHeader GrayVol # TableCol 4 FieldName Gray Matter Volume # TableCol 4 Units mm^3 # TableCol 5 ColHeader ThickAvg # TableCol 5 FieldName Average Thickness # TableCol 5 Units mm # TableCol 6 ColHeader ThickStd # TableCol 6 FieldName Thickness StdDev # TableCol 6 Units mm # TableCol 7 ColHeader MeanCurv # TableCol 7 FieldName Integrated Rectified Mean Curvature # TableCol 7 Units mm^-1 # TableCol 8 ColHeader GausCurv # TableCol 8 FieldName Integrated Rectified Gaussian Curvature # TableCol 8 Units mm^-2 # TableCol 9 ColHeader FoldInd # TableCol 9 FieldName Folding Index # TableCol 9 Units unitless # TableCol 10 ColHeader CurvInd # TableCol 10 FieldName Intrinsic Curvature Index # TableCol 10 Units unitless
We can expect to see the Structure Name, Number of Vertices, Surface Area, Gray Matter Volume, Average Thickness, Thickness StDev, Integrated Rectified Mean Curvature, Integrated Rectified Gaussian Curvature, Folding Index and Intrinsic Curvature Index for each entry in the table.
The remainder of the table shows this information for all the structures that are labeled in the aseg:
# ColHeaders StructName NumVert SurfArea GrayVol ThickAvg ThickStd MeanCurv GausCurv FoldInd CurvInd unknown 15085 10384 21630 2.006 1.096 0.123 0.038 168.313 26.766 bankssts 1126 770 1563 2.132 0.462 0.103 0.024 7.056 1.004 caudalanteriorcingulate 931 636 2125 2.721 0.675 0.127 0.031 15.801 0.991 caudalmiddlefrontal 3577 2403 6575 2.447 0.535 0.120 0.028 34.901 3.674 corpuscallosum 1035 680 1215 2.123 0.902 0.136 0.023 17.731 0.799 cuneus 2966 1958 3769 1.740 0.473 0.140 0.033 37.320 3.630 entorhinal 683 419 1620 2.819 0.632 0.090 0.021 5.349 0.429 fusiform 6622 4607 11486 2.190 0.634 0.130 0.032 77.276 7.884 . . . .
Group stats files
This section will run you through using the stats directory in the subjects to perform group stats of certain structures that may be of interest to your study. The following commands will help you combine the data of the subjects you are analyzing into one table that will be easily read into a spreadsheet program. We have considered 6 subjects as examples (004, 021, 040, 067, 080, 092) in the following sections.
Set your SUBJECTS_DIR to the location where you have your subjects to be analyzed.
Table of segmentation volumes
This section explains how to create a table of segmentation volumes using the 6 subjects mentioned above.
asegstats2table --subjects 004 021 040 067 080 092 \ --segno 11 17 18 \ --t aseg.vol.table
where 11, 17 and 18 correspond to the segmentation label of left caudate, left hippocampus and left amygdala respectively. You can get the segmentation labels and the corresponding subcortical structures using the following command.
less $FREESURFER_HOME/FreeSurferColorLUT.txt
To load the resulting table into a spreadsheet, run
oocalc aseg.vol.table
and then select Space in the Separated by menu.
Please note that the oocalc command is meant to be run on a Linux machine. In the table, the first cell is volume indicating that the measure is a volume in mm3. In addition to segmentations, you can also get IntraCranialVol (ICV) and BrainSegVol into the table.
About the subject IDs, you'll notice that in the examples we've considered here, each subject is a 3 digit number. Therefore oocalc thinks it is a number and removes leading 0s. This is an oocalc issue but probably it would not happen if subject names has characters in them instead of integers.
Table of segmentation mean intensities
Purpose of this section is to demonstrate how you can change the measure from volume to mean intensity using asegstats2table command.
asegstats2table \ --subjects 004 021 040 067 080 092 \ --segno 11 17 18 \ --meas mean \ --t aseg.mean-intensity.table
You can load the table into a spread sheet as explained in the previous section. Please refer to the file FreeSurferColorLUT.txt for the segmentation labels and the corresponding subcortical structures.
less $FREESURFER_HOME/FreeSurferColorLUT.txt
Table of white matter parcellation volumes
The purpose of this section is to show how you can change the segmentation atlas
asegstats2table \ --subjects 004 021 040 067 080 092 \ --segno 3007 3021 3022 4022 \ --stats wmparc.stats \ --t wmparc.vol.table
Please refer to the file FreeSurferColorLUT.txt for the segmentation labels and the corresponding subcortical structures.
less $FREESURFER_HOME/FreeSurferColorLUT.txt
Table of the surface area of each cortical parcellation in the Desikan atlas
This section explains how to create a table of the surface area of each cortical parcellation in the Desikan atlas.
aparcstats2table --hemi lh \ --subjects 004 021 040 067 080 092 \ --t lh.aparc.area.stats
Table of the average thickness of each cortical parcellation in the Destrieux atlas
The purpose of this section is to show how to change the summary measure and the parcellation atlas.
aparcstats2table --hemi lh \ --subjects 004 021 040 067 080 092 \ --meas thickness \ --parc aparc.a2005s \ --t lh.aparc.a2005.thickness.stats