Brain Images of Normal Subjects (BRAINS) Bank Background Background MR Image processing Brain extraction

Brain Images of Normal Subjects (BRAINS) Bank Background Background MR Image processing Brain extraction www.phwiki.com

Brain Images of Normal Subjects (BRAINS) Bank Background Background MR Image processing Brain extraction

Hawkins, Dave, News Director;Host has reference to this Academic Journal, PHwiki organized this Journal Brain Images of Normal Subjects (BRAINS) Bank David Alex in addition to er Dickie Dr Dominic E. Job Background Age in addition to 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 in addition to atlases calculate distributions (not assume) Data requires much image processing Pilot ~200 normal, ~200 AD sjbs, 60-94 years

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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 in addition to distribution Trans as long as mations 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 in addition to distribution Trans as long as mations lose natural data, smoothing Image banks support data driven models BRAINS atlases BRAINS MNI 152 Image registration

BRAINS atlases 1 0 BRAINS atlases Alzheimer’s Normal Red=95th

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White matter lesions White matter lesions 95 75 50 25 5 A Percentile

White matter lesions 95 75 50 25 5 A Percentile Percentiles of grey matter density in a normal ageing in addition to Alzheimer’s disease subject Alzheimer’s Normal 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 in addition to Alzheimer’s disease subject Alzheimer’s Normal Alzheimer’s disease has lowest percentiles of GM in MTL

SINAPSE SPIRIT, MRC, Tony Watson Thank you

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Hawkins, Dave is from United States and they belong to KGMN-FM and they are from  Kingman, United States got related to this Particular Journal. and Hawkins, Dave deal with the subjects like Local News; National News; Regional News

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