This is a collection of handy helper functions for MRI data analysis. Link to medium post: https://zapaishchykova.medium.com/preprocessing-mri-in-python-4d67c291b8f3
- (optional) Converting from DICOM to nifty ( in case you got "raw" data)
- Image registration
- Image rescaling
- (optional) Skull stripping if you are working with brains
- (optional) N4 Bias field correction
- Image normalization, filtering, binning
- (option) converting from 3D to 2D slices
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Clone repo
git clone
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To create an enviroment, run:
conda env create -f environment.yml
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To activate the enviroment:
conda activate mri_toolkit
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To run the example, open notebook example.ipynb:
jupyter notebook
MRI data of 3-12 year old children and adults during viewing of a short animated film. The data is available at https://openfmri.org/dataset/ds000228/