Introduction to FreeSurfer surfer.nmr.mgh.harvard

Introduction to FreeSurfersurfer.nmr.mgh.harvard.edu

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.

ICBM Atlas

Why not just register to an ROI Atlas?

12 DOF(Affine)

Subject 1 Subject 2 aligned with Subject 1 (Subject 1’s Surface)

Problems with Affine (12 DOF) Registration

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

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

Surfaces: White and Pial

Cortical Thickness

white/gray surface

pial surface

lh.thickness, rh.thickness

• Distance between white and pial surfaces

• One value per vertex

A Surface-Based Coordinate System

Comparing Coordinate Systems and Brodmann Areas

Cumulative histogram (red=surface, blue=nonlinear

Talairach)

Ratio of surface accuracy to volume accuracy

Automatic Surface Segmentation

Precentral Gyrus Postcentral Gyrus

Superior Temporal GyrusBased on individual’s folding pattern

Inter-Subject AveragingS

ubje

ct 1

Sub

ject

2

Native Spherical Spherical

Surface-to- Surface

Surface-to- Surface

GLM

Demographics

mri_glmfit cf. Talairach

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

Talk Outline

1. Cortical (surface-based) Analysis.

2. Volume Analysis.

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)!

Volumetric Segmentation (aseg)

Caudate

Pallidum

Putamen

Amygdala

Hippocampus

Lateral Ventricle

Thalamus

White Matter

Cortex

Not Shown:Nucleus AccumbensCerebellum

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