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Imaging Data Fusion
Fusion of different modalities is beneficial to better correlate between the results of the various analyses. After coregistration of sMRI with fMRI and PET, the images are normalized into the common MNI space. This allows us to create average spaces unique to the study
Average Space and Fusion Templates
Montreal Neurological Institute (MNI) Space
The MNI space is a 3D coordinate grid template which is used to map location of different brain regions. Both fMRI and PET are warped and aligned into the MNI space via coregistration and normalization, thus removing the individual differences in the size and overall shape of the brain
DARTEL Space
Diffeomorphic Anatomical Registration Template using Exponentiated Lie algebra (DARTEL). These are templates of the average segmented structure unique to the study. Two templates are generated: one for gray matter, and another for white matter
Population Average Space
This is a template showing the combined average structure unique to the study. The template is used as a background for functional images during visualization
Mean and Skeletonized Diffusion Tracts
These are the results of the tract-based spatial statistics, showing the mean diffusion and anisotropy of the white matter tracts
Mean Standard Uptake Value Space
This is a template of the mean SUV measured per voxel
MRI-PET Fusion Templates
These are templates obtained by shooting the individual PET images to a) the gray matter DARTEL, b) white matter DARTEL, or c) population average space
Normative Modeling and the Role of AI
From the templates, certain features can be extracted such as total intracranial volume (TIV), GM and WM volumes, cortical thickness, etc. These features can be analyzed separately, or fed to an artificial neural network (ANN) that may be able to: a) provide normative templates for phenotyping, or b) identify biomarkers for various neurological disorders
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