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Gist 0efb8d4b7f4538ca9efc78832536d0c3

✓ Published0🌍 Public
Aakeshavan
Last edited Jan 24, 2018
Created on Jan 24, 2018

This visualization compares MRIQC automated quality metrics with manual voting results for T1-weighted brain scans. It processes JSON vote data from multiple raters, consolidating their quality assessments into a pandas DataFrame. The example demonstrates how to aggregate and inspect manual quality-control annotations alongside automated MRIQC scores, using pandas for data manipulation and matplotlib for inline plotting in a Jupyter notebook.

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