In automatic subcortical segmentation, each voxel in the normalized brain volume is assigned one of about 40 labels, including:
- Cerebral White Matter, Cerebral Cortex, Lateral Ventricle, Inferior Lateral Ventricle, Cerebellum White Matter, Cerebellum Cortex, Thalamus, Caudate, Putamen, Pallidum, Hippocampus, Amygdala, Lesion, Accumbens area, Vessel, Third Ventricle, Fourth Ventricle, Brain Stem, Cerebrospinal Fluid
The automatic subcortical segmentation can take many (11+) hours to complete.
To view just the segmentation, use this command:
tkmedit <subject name> norm.mgz -aseg
Float your cursor over any voxel and the label assigned to it will be displayed in the TkMeditTools window.
If the voxels are incorrectly labeled, then you can re-label them yourself although we suggest contacting the freesurfer mailing list first to see if there is an automatic procedure that can be used to re-label them.. Refer to the TkMeditGuide/TkMeditWorkingWithData/TkMeditSelectionsLabels page for detailed information on manually editing the aseg.
Automatic subcortical segmentation of a brain volume is based upon the existence of an atlas containing probablistic information on the location of structures. This is decribed here:
Whole Brain Segmentation: Automated Labeling of Neuroanatomical Structures in the Human Brain, Fischl et al., (2002). Neuron, 33:341-355.
The atlas included with the Freesurfer distribution is found in the 'average' directory, and is called 'RB_all_2008-03-26.gca'. It is possible to construct your own atlas. This is described next.
Constructing an Aseg Atlas
- Using tkmedit, label each volume in the brain. Repeat for all subjects to be included in the atlas.
Run mri_ca_train to create the atlas.
See also rebuild_gca_atlas.csh script in $FREESURFER_HOME/bin.
See also AtlasSubjects
For accuracy evaluations see also SubcorticalSegmentationAccuracy