Automated Amygdala Surface Modeling Pipeline - PowerPoint PPT Presentation

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Automated Amygdala Surface Modeling Pipeline

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FreeSurfer can be used to automatically segment amygdala and hippocampus. ... Spherical coordinate system for amygdala surface ... – PowerPoint PPT presentation

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Title: Automated Amygdala Surface Modeling Pipeline


1
Automated Amygdala Surface Modeling Pipeline
  • Moo K. Chung
  • Department of Biostatistics and Medical
    Informatics
  • Waisman Laboratory for Brain Imaging and Behavior
  • University of Wisconsin-Madison
  • www.stat.wisc.edu/mchung/research/amygdala

Matlab-based image processing/analysis/visualizat
ion tools
2
Acknowledgments
  • Brendon, M. Nacewicz, Anqi Qiu, Shubing Wang, Kim
    M. Dalton, Jamie Hanson, Seth Pollak, Richard J.
    Davidson
  • Waisman laboratory for brain imaging and behavior
  • University of Wisconsin-Madison

3
Amygdala manual segmentation
Left amygdala of subject 001
FreeSurfer can be used to automatically segment
amygdala and hippocampus. Publications coming out
in NeuroImage using FreeSurfer segmentation.
4
Traditional Volumetry
There is no volume difference in autism vs.
control (study 1 (n24) study 3 (n23)
combined) Left (p0.64) Right (p0.81) Can we
still have localized difference?
5
Step13D model of left amygdala of subject 001
top
Orientation
bottom
left
back
front
middle
6
3D model of left amygdala of subject 001
top
top
middle
bottom
left
bottom
left
middle
front
front
back
back
7
Spherical coordinate system for amygdala surface
Step 2
Analysis surface registration will be done on a
sphere and the result will be back projected onto
the average amygdala surface.
8
Hotellings T-square test on group difference
Left
Right
front
back
middle
left
right
middle
Origami representation
9
Keith Worsleys SurfStat MATLAB package
Testing Group difference controlling for Brain
size and Age
slm SurfStatLinMod(disp, Brain Age
Group,avsurf) slm SurfStatT(slm, group)
gtpvalue 0.001 0.005 0.01 0.05
0.1 gtthresholdrandomfield_threshold(slm,
pvalue) pvalue 0.0010 0.0050 0.0100
0.0500 0.1000 threshold 6.8058
6.2154 5.9564 5.3398 5.0635
Corrected P-value thresholding using the random
field theory
10
Significance of group difference controlling for
Brain size and Age
Left
Right
front
back
3.7
middle
left
right
middle
Max T 3.7970 Random field thresholding at 0.05
level 5.3398
Max T 3.6687 Random field thresholding at 0.05
level 5.3200
0
T-stat.
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