Brain Images of Normal Subjects (BRAINS) Bank David Alexander Dickie Dr Dominic E. Job.
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Transcript of Brain Images of Normal Subjects (BRAINS) Bank David Alexander Dickie Dr Dominic E. Job.
Brain Images of Normal Subjects (BRAINS) Bank
David Alexander Dickie
Dr Dominic E. Job
Background
• Age and disease affect brain structure
• The effects are disparate
• Much MRI data are needed
• ~300 normal ageing (>60yrs) subjects
• “Atlases” of the aged brain are limited
Background
• Brain Images of Normal Subjects (BRAINS) bank >1000 normal sbjs >60yrs
• BRAINS models and atlases calculate distributions (not assume)
• Data requires much image processing– Pilot ~200 normal, ~200 AD sjbs, 60-94 years
MR Image processing
Brain extraction
Brain extraction
• Brain Extraction Tool (BET) commonly used
Brain extraction
• Brain Extraction Tool (BET) commonly used
Template based brain extraction
• Advanced Normalization Tools (ANTS) http://www.picsl.upenn.edu/ANTS/
• Uses diffeomorphic (super nonlinear) spatial normalisation
Image registration
ANTS diffeomorphic spatial normalisation
ANTS diffeomorphic spatial normalisation
ANTS diffeomorphic spatial normalisation
• But catastrophes still happen
ANTS diffeomorphic spatial normalisation
• ANTS takes ~1 hour per subject (computer)
• Still requires by slice checking– ~10 minutes checking per subject
• 460 subjects took ~2.5 months
• Catastrophes still happen
• >1000 subjects in full-scale study
Data driven brain volume models
• Statistical models oft used in brain imaging– The general linear model (GLM)
• Assume data generation and distribution
• Transformations lose natural data, have risks, complexity
• Image banks support data driven models
Brains are heteroscedastic
See, they’re different
Data driven vs. general models
DDPM has ~65% less error
Data driven brain voxel models
• Statistical voxel based morphometry (VBM)– The general linear model (GLM)
• Assumes data generation and distribution
• Transformations lose natural data, smoothing
• Image banks support data driven models
BRAINS atlasesBRAINS
MNI 152
Image registration
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0
BRAINS atlases
BRAINS atlases
Alzheimer’sNormal
Red=95th
White matter lesions
White matter lesions
95
75
50
25
5 A
Percentile
95
75
50
25
5 A
Percentile
White matter lesions
Percentiles of grey matter density in a normal ageing and Alzheimer’s disease subject
Alzheimer’sNormal
Alzheimer’s disease has lowest percentiles of GM in MTL
5th
95th
50th
25th
75th
Percentile
Bad
OK
Good
Percentiles of grey matter density in a normal ageing and Alzheimer’s disease subject
Alzheimer’sNormal
Alzheimer’s disease has lowest percentiles of GM in MTL
Alzheimer’s Control
5th
95th
50th
25th
75th
Percentile
Median percentile image of grey matter density in Alzheimer’s disease (n=49) and control (n=49) subjects
Alzheimer’s has lowest percentiles of GM across the cortex, specifically hippocampus.
BRAINS vs. VBM
BRAINS vs. VBM
• Needs data
• Less assumptions
• Anatomical resolution
• Specific anatomy
• Individuals
• Size of differences
• Simpler
SINAPSE SPIRIT, MRC, Tony Watson
Thank you