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Neuroimaging Introduction
Feature Group MeetingAugust 16, 2012
Introduction
• The Human Brain– What are we trying to look at?
• Modalities– How do we measure?
• Data• The Informatics Landscape– Processing Pipeline– Why?
The Human Brain
3 lbs109 neurons1015 synaptic connections
Measuring Structure and Function
Invasive Non-invasive
Structure
sMRI
CT
DTI
Function
fMRI
PET
EEG
MEGMODALITIES
Measuring Structure and Function
? Population Protocol Data
What happens to the structure of region X as we get older?What is my brain doing when I see pictures of cats?Which regions are working together?
? Public Repository
MODALITIES
Measuring Structure and Function
Invasive Non-invasive
Structure
sMRI
CT
DTI
Function
fMRI
PET
EEG
MEGMODALITIES
Measuring Structure and Function
Invasive Non-invasive
Structure
sMRI
CT
DTI
Function
fMRI
PET
EEG
MEGMODALITIES
MODALITIES © 2008 HowStuffWorks.com
What does an image look like?
DATA
SLICE
VOXEL
AXIAL SAGGITAL CORONAL
Structural Data• T1 weighted
– TR: short– TE: short– Fat: bright– Fluid: dark
• T2 weighted– TR: long– TE: long– Fat: intermediate-bright– Fluid: bright
DATA
Functional Data
DATA
What do the files look like?
DATA
P FilesImaging Data
HeaderNifti
• .nii (one file)• .img / .hdr combo
3D
• .nii.gz (compressed file)• .nii (uncompressed)• .img/.hdr combos
4D
Segmentation
Realign / Reslice
Motion Correction
Segmentation Smoothing Filtering
fMRI Processing Pipeline
ANALYSIS
Registration
Normalization
Statistical Test
Segmentation
Realign / Reslice
Motion Correction
Segmentation Smoothing Filtering
Data Driven Approaches?
ANALYSIS
Registration
Normalization
?
Data Driven Approaches?
ANALYSIS
• Connectivity Analysis– Seed-based– Matrix Decomposition (ICA)
Independent Component Analysis (ICA)
ANALYSIS
• One 3D image [ v1 v2 v3 v4… v4 ]• 4D Image Matrix, M
v1 v2 v3 v4 v5 v6 v7 . . . vn
Voxels
Time
Independent Component Analysis (ICA)
http://www.fmrib.ox.ac.uk/fsl/melodic/index.htmlANALYSIS
n x m n x n n x m
n time pointsm voxels
3D image flattened, all voxels at T =1 Components spatial map
Independent Component Analysis (ICA)
http://www.fmrib.ox.ac.uk/fsl/melodic/index.htmlANALYSIS
n x m n x n n x m
Independent Component Analysis (ICA)
http://www.fmrib.ox.ac.uk/fsl/melodic/index.htmlANALYSIS
• Features• Classification
– Noise vs. “real”– Network X vs Y– ADHD vs control
SPATIAL
TIMECOURSEPATTERNS OF NETWORKS
Informatics Landscape
INFORMATICS LANDSCAPE
Analysis Method
Public Data Process Machine
Learning
Disorder diagnosisClassification of subtypes of diseaseImproved filtering methodsUnderstanding human connectome
Why?
