Subject-wise networks from structural MRI, both vertex- and voxel-wise features (thickness, GM density, curvature, gyrification)
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Updated
Apr 26, 2024 - Jupyter Notebook
Subject-wise networks from structural MRI, both vertex- and voxel-wise features (thickness, GM density, curvature, gyrification)
Computational Anatomy Toolbox for SPM12
DL DiReCT - Direct Cortical Thickness Estimation using Deep Learning-based Anatomy Segmentation and Cortex Parcellation
This is where I describe the surface-based cortical thickness workflows that I have learned to use.
Sphere2dice converts Cortical Brain Morphometry data from FreeSurfer or Gifty type into a stack of 2D images and saves is as numpy array. This stack of images is easier to use as input to conventional CNNs, while avoiding projection issues other methods suffer from.
Flywheel gear wrapping the ANTs Cortical Thickness pipeline.
Age-related changes in Cortical Thickness in Autism
Software pipeline for generating heatmaps of cortical thickness abnormalities in patients across the age spectrum.
Flywheel gear for generating heatmaps of cortical thickness abnormalities in aging patients.
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