Transcript LZ.freesurfer.intro

Introduction to FreeSurfer
http://surfer.nmr.mgh.harvard.edu
Post Your Questions!
http://surfer.nmr.mgh.harvard.edu/cgi-bin/fsurfer/questions.cgi
Why FreeSurfer?
•
•
•
Anatomical analysis is not like functional
analysis – it is completely stereotyped.
Registration to a template (e.g.
MNI/Talairach) does not account for
individual anatomy.
Even if you do not care about the anatomy,
anatomical models allow functional analysis
not otherwise possible.
3
Why not just register to an ROI
Atlas?
12 DOF
(Affine)
ICBM Atlas
4
Problems with Affine (12 DOF)
Registration (you will get sick of this slide)
Subject 1
Subject 2 aligned with Subject 1
(Subject 1’s Surface)
5
Surface and Volume Analysis
Cortical Reconstruction
and Automatic Labeling
Surface Flattening
Inflation and Functional
Mapping
Automatic Subcortical
Gray Matter Labeling
Surface-based Inter-subject Automatic Gyral White
Alignment and Statistics
Matter Labeling
6
Talk Outline
1. Cortical (surface-based) Analysis.
2. Volume Analysis.
7
Talk Outline
1. Cortical (surface-based) Analysis.
2. Volume Analysis.
Why Is a Model of the Cortical
Surface Useful?
Local functional organization of cortex is largely 2dimensional! Eg, functional mapping of primary visual areas:
From (Sereno et al, 1995, Science).
Also, smooth along surface
Flat Map of Monkey Visual Areas
D.J. Felleman and D.C. Van Essen, CC, 1991
10
What Can One Do With A Surface
Model?
goal: use model to impose desired activity pattern on V1
desired shape of activity pattern
required shape of stimulus
w=k log(z+a)
left primary visual cortex
Collaboration with Jon Polimeni and Larry Wald.
right visual hemifield
11
Tangential Resolution Measured
with Surface-based Analysis
Collaboration with Jon Polimeni and Larry Wald.
12
Tangential Resolution Measured
with Surface-based Analysis
Collaboration with Jon Polimeni and Larry Wald.
13
M-G-H
14
Thanks to Larry Wald for this slide.
Surfaces: White and Pial
15
Inflation
16
Surface Flattening – Whole
Hemisphere
central
anterior
sylvian
Inflated surface with cuts
superior temporal
posterior
calcarine
Metrically optimal flat map
17
Surface Model
• Mesh of triangles gives a measurable
size
• Allows us to measure Area, Curv.,
Thickness (distance b/w vertices)
• Vertex = point of 6 triangles
• Triangles/Faces ~ 150,000 per hemi
• 1:1 correspondence of vertices
• XYZ at each vertex
18
Cortical Thickness
• Distance between
white and pial surfaces
• One value per vertex
pial surface
white/gray surface
lh.thickness, rh.thickness
19
A Surface-Based Coordinate
System
20
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 Gyrus
Based on individual’s folding pattern
22
Inter-Subject Averaging
Spherical
Spherical
GLM
Subject 1
Native
Subject 2
Demographics
Surface-toSurface
Surface-toSurface
mri_glmfit
cf. Talairach
23
Visualization
24
Borrowed from (Halgren et al., 1999)
Rosas et al., 2002
Sailer et al., 2003
Kuperberg et al., 2003
Fischl et al., 2000
Gold et al., 2005
Salat et al., 2004
Rauch et al., 2004
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)!
27
Volumetric Segmentation (aseg)
Cortex
White Matter
Lateral Ventricle
Thalamus
Caudate
Pallidum
Putamen
Amygdala
Hippocampus
Not Shown:
Nucleus Accumbens
Cerebellum
28
Volume Differences Predictive of AD
lateral-ventricle volume (pct brain)
2.5
2
1.5
1
0.5
0
LH
RH
blue=ctrl (25), cyan=questbl (71), y=converters (21), red=AD (17)
Data courtesy of Drs Marilyn Albert and Ron Killiany
Combined Segmentation
aparc
aparc+aseg
aseg
30
Gyral White Matter Segmentation
+
+
aparc+aseg
wmparc
Nearest Cortical Label
to point in White Matter
aparc
31
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
32
Acknowledgements
MGH
MGH
MIT
Bruce Fischl
Allison Stevens
Nick Schmansky
Andre van der Kouwe
Doug Greve
David Salat
Evelina Busa
Lilla Zöllei
Koen Van Leemput
Sita Kakunoori
Ruopeng Wang
Rudolph Pienaar
Krish Subramaniam
Diana Rosas
Jean Augustinack
Polina Golland
B. T. Thomas Yeo
Mert Sabuncu
Florent Segonne
Peng Yu
Ramesh Sridharan
Martin Reuter
Anastasia Yendiki
Jon Polimeni
Kristen Huber
MGH (past)
Brian T Quinn
Xiao Han
Niranjini Rajendran
Jenni Pacheco
UC San Diego
Anders Dale
UCL
Marty Sereno
Sylvester Czanner
Gheorghe Postelnicu
Sean Marrett
33
NINDS