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| [wiki:Self:FreeSurferWorkFlows top] | [wiki:Self:HistoricalReconstruction previous] | [[FreeSurferWorkFlows|top]] |
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| = FreeSurfer Subcortical Segmentation = | = Subcortical Segmentation = |
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| FreeSurfer now automatically runs automated labeling of the brain volume and this is included in all versions of the September 2005 release. In subcortical segmentation, each voxel in the normalized brain volume is assigned one of about 40 labels, including: | In automatic subcortical segmentation, each voxel in the normalized brain volume is assigned one of about 40 labels, including: |
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| 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, Central Diencephalon, Third Ventricle, Fourth Ventricle, Brain Stem, Cerebrospinal Fluid |
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 |
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| However, if you processed your anatomical data using previous versions, you can just run the subcortical segmentation separately if you wish to obtain the automated labels. The September 2005 release of FreeSurfer by default uses the automatically segmented brain volume (ASEG) to segment the white matter volume (WM). You will use the -noedit_wm_with_aseg flag to ensure that it preserves and uses the white matter volume (WM) edits that you made. | FreeSurfer runs automated labeling of the brain volume [[ReconAllDevTable|during the -autorecon2 stage]]. The automatic subcortical segmentation can take many (11+) hours to complete. |
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| To view just the segmentation, use this command: |
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| recon-all -autorecon2 -noedit_wm_with_aseg -keepwmedits -subjid <subject name> | tkmedit <subject name> norm.mgz -aseg |
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| == Process Flow == | Float your cursor over any voxel and the label assigned to it will be displayed in the TkMeditTools window. |
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| ||<rowbgcolor='#80FF80'>'''recon-all step'''||'''Input'''||'''Command Line'''||'''Output'''|| ||<|10(bgcolor='#FFFFE0'>["recon-all"] -autorecon1 -subjid subj|| ||<rowbgcolor='#E0E0FF'>orig/001.mgz||<|2(>["mri_motion_correct2"] -i orig/001.mgz -i orig/002.mgz -o rawavg.mgz||<|2(>rawavg.mgz|| ||<rowbgcolor='#E0E0FF'>orig/002.mgz|| ||<rowbgcolor='#E0E0FF'>rawavg.mgz||["mri_convert"] rawavg.mgz orig.mgz --conform||orig.mgz|| ||<rowbgcolor='#E0E0FF'>orig.mgz||["mri_convert"] orig.mgz orig.mnc||orig.mnc|| ||<rowbgcolor='#E0E0FF'>orig.mnc||(4 iterations of) ["nu_correct"] -clobber nu0.mnc nu1.mnc||nu4.mnc|| ||<rowbgcolor='#E0E0FF'>nu4.mnc||["mri_convert"] nu4.mnc nu.mgz||nu.mgz|| ||<rowbgcolor='#E0E0FF'>nu.mgz||["talairach2"] subjid -mgz||transforms/talairach.xfm|| ||<rowbgcolor='#E0E0FF'>nu.mgz||["mri_normalize"] nu.mgz T1.mgz||T1.mgz|| ||<rowbgcolor='#E0E0FF'>T1.mgz||["mri_watershed"] T1.mgz brain.mgz||brain.mgz|| ||<-4(rowbgcolor='#FF8080'>Check skullstrip (brain.mgz), talairach (transforms/talairach.xfm), and normalization (brain.mgz or T1.mgz - mean wm voxel value = 110)|| ||<|35(bgcolor='#FFFFE0'>["recon-all"] -autorecon2 -no_edit_wm_with_aseg -keepwmedits -subjid subj|| ||<rowbgcolor='#E0E0FF'>brain.mgz||<|2(>["mri_em_register"] -mask brain.mgz -p .5 -fsamples fsamples.mgz nu.mgz $GCA transforms/talairach.lta||<|2(>transforms/talairach.lta|| ||<rowbgcolor='#E0E0FF'>nu.mgz|| ||<rowbgcolor='#E0E0FF'>brain.mgz||<|3(>["mri_ca_normalize"] -mask brain.mgz nu.mgz $GCA transforms/talairach.lta norm.mgz||<|3(>norm.mgz|| ||<rowbgcolor='#E0E0FF'>nu.mgz|| ||<rowbgcolor='#E0E0FF'>transforms/talairach.lta|| ||<rowbgcolor='#E0E0FF'>brain.mgz||<|3(>["mri_ca_register"] -cross-sequence -mask brain.mgz -T transforms/talairach.lta norm.mgz $GCA transforms/talairach.m3z||<|3(>transforms/talairach.m3z|| ||<rowbgcolor='#E0E0FF'>transforms/talairach.lta|| ||<rowbgcolor='#E0E0FF'>norm.mgz|| ||<rowbgcolor='#E0E0FF'>norm.mgz||<|2(>["mri_ca_label"] -cross-sequence norm.mgz transforms/talairach.m3z $GCA aseg.mgz||<|2(>aseg.mgz|| ||<rowbgcolor='#E0E0FF'>transforms/talairach.m3z|| ||<rowbgcolor='#E0E0FF'>brain.mgz||<|2(>["mri_normalize"] -mask brain.mgz nu.mgz T1.mgz||<|2(>T1.mgz|| ||<rowbgcolor='#E0E0FF'>nu.mgz|| ||<rowbgcolor='#E0E0FF'>T1.mgz||<|2(>["mri_mask"] T1.mgz brain.mgz brain.mgz||<|2(>brain.mgz|| ||<rowbgcolor='#E0E0FF'>brain.mgz|| ||<rowbgcolor='#E0E0FF'>brain.mgz||["mri_segment"] brain.mgz wm.mgz||wm.mgz|| ||<rowbgcolor='#E0E0FF'>wm.mgz||<|2(>["mri_edit_wm_with_aseg"] wm.mgz aseg.mgz wm.mgz||<|2(>wm.mgz|| ||<rowbgcolor='#E0E0FF'>aseg.mgz|| |
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. = Aseg Atlas = 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: * [[https://surfer.nmr.mgh.harvard.edu/ftp/articles/fischl02-labeling.pdf|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 = Basic steps: * 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 = References = The original CMA segmentation scheme used for subcortical segmentation training is defined by (Filipek, et al, Cerebral Cortex, 1994) ([[https://www.ncbi.nlm.nih.gov/pubmed/7950308|paper]]). However, with better imaging resolution, anatomists Verne Caviness and Nikos Mkris developed the separation of the "thalamus proper" from a "ventral diencephalon" region that subtends many of the smaller nuclei and structures in the area inferior to the thalamus, such as hypothalamus, red nuclei, later and medial geniculate, ect. The first definition of the ventral diencephalon method is provided in Am J Med Genet. 1997 Sep 19;74(5):507-14. ([[https://www.ncbi.nlm.nih.gov/pubmed/9342202|paper]]). |
Subcortical Segmentation
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
FreeSurfer runs automated labeling of the brain volume during the -autorecon2 stage.
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.
Aseg Atlas
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
Basic steps:
- 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
References
The original CMA segmentation scheme used for subcortical segmentation training is defined by (Filipek, et al, Cerebral Cortex, 1994) (paper). However, with better imaging resolution, anatomists Verne Caviness and Nikos Mkris developed the separation of the "thalamus proper" from a "ventral diencephalon" region that subtends many of the smaller nuclei and structures in the area inferior to the thalamus, such as hypothalamus, red nuclei, later and medial geniculate, ect. The first definition of the ventral diencephalon method is provided in Am J Med Genet. 1997 Sep 19;74(5):507-14. (paper).