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Why FreeSurfer?
1. Anatomical analysis is not like functional analysis – it is completely stereotyped.
2. Registration to a template (e.g. MNI/Talairach) doesn’t account for individual anatomy.
3. Even if you don’t care about the anatomy, anatomical models allow functional analysis not otherwise possible.
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ICBM Atlas
Why not just register to an ROI Atlas?
12 DOF(Affine)
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Subject 1 Subject 2 aligned with Subject 1 (Subject 1’s Surface)
Problems with Affine (12 DOF) Registration
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Surface and Volume Analysis
Cortical Reconstructionand Automatic Labeling
Inflation and FunctionalMapping
Surface FlatteningSurface-based IntersubjectAlignment and Statistics
Automatic SubcorticalGray Matter Labeling
Automatic Gyral White Matter Labeling
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Talk Outline
1. Cortical (surface-based) Analysis.
2. Volume Analysis.
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Surface Reconstruction Overview
• Input: T1-weighted (MPRAGE,SPGR)• Find white/gray surface• Find pial surface• “Find” = create mesh
– Vertices, neighbors, triangles, coordinates– Accurately follows boundaries between tissue types– “Topologically Correct”
• closed surface, no donut holes• no self-intersections
• Generate surface-based cross-subject registration• Label cortical folding patterns• Subcortical Segmentation along the way
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Surface Model
• Mesh (“Finite Element”)• Vertex = point of triangles
• Neighborhood
• XYZ at each vertex
• Triangles/Faces ~ 150,000
• Area, Distance
• Curvature, Thickness
• Moveable
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Surfaces: White and Pial
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Cortical Thickness
white/gray surface
pial surface
lh.thickness, rh.thickness
• Distance between white and pial surfaces
• One value per vertex
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A Surface-Based Coordinate System
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Comparing Coordinate Systems and Brodmann Areas
Cumulative histogram (red=surface, blue=nonlinear
Talairach)
Ratio of surface accuracy to volume accuracy
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Automatic Surface Segmentation
Precentral Gyrus Postcentral Gyrus
Superior Temporal GyrusBased on individual’s folding pattern
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Inter-Subject AveragingS
ubje
ct 1
Sub
ject
2
Native Spherical Spherical
Surface-to- Surface
Surface-to- Surface
GLM
Demographics
mri_glmfit cf. Talairach
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Borrowed from (Halgren et al., 1999)
Visualization
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Automatic Cortical Parcellation
Fine-tune based onindividual anatomy
Spherical Atlas based on Manual Parcellations (40 of them)
Map to IndividualThru Spherical Reg
Note: Similar methodology to volume labeling
More in the Anatomical ROI talk
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Talk Outline
1. Cortical (surface-based) Analysis.
2. Volume Analysis.
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Volume Analysis: Automatic Individualized Segmentation
Surface-based coordinate system/registration appropriate for cortex but not for thalamus, ventricular system, basal ganglia, etc…
Anatomy is extremely variable – measuring the variance and accounting for it is critical (more in the individual subject talk)!
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Volumetric Segmentation (aseg)
Caudate
Pallidum
Putamen
Amygdala
Hippocampus
Lateral Ventricle
Thalamus
White Matter
Cortex
Not Shown:Nucleus AccumbensCerebellum
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Summary• Why Surface-based Analysis?
– Function has surface-based organization– Visualization: Inflation/Flattening– Cortical Morphometric Measures– Inter-subject registration
• Automatically generated ROI tuned to each subject individually
Use FreeSurfer Be Happy
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FreeSurfer Directory Tree
bert
scripts surf label mri stats
orig.mgz T1.mgz brain.mgz wm.mgz aseg.mgz
•Subject•Subject Name
Each data set has its own unique SubjectId (eg, bert)
recon-all –i file.dcm –subject bert –all
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Other File Formats• Surface: Vertices, XYZ, neighbors (lh.white)• Curv: lh.curv, lh.sulc, lh.thickness• Annotation: lh.aparc.annot• Label: lh.pericalcarine.label• Unique to FreeSurfer • FreeSurfer can read/write:
• NIFTI, Analyze, MINC• FreeSurfer can read:
• DICOM, Siemens IMA, AFNI