Gist 0c28ed2b6d7235146517

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Gist 0c28ed2b6d7235146517

✓ Published0🌍 Public

Last edited Jul 11, 2014

Created on Jul 8, 2014

This example visualizes intraclass correlations for within- and between-site reliability of brain volume estimates from Freesurfer and SIENAX across multicenter MS study scans. It presents a pandas DataFrame table of scanning parameters and reliability metrics for nine scanners at six sites. The code uses IPython’s `%pylab inline` for interactive plotting, pandas for tabular data handling, and nipype’s `loadpkl` to load the analysis results. The visualization is built in a Jupyter notebook with Vue integration, showing how heterogeneous acquisition protocols affect measurement consistency.

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