QAP v1.0.8

• QAP measure outputs and NIFTI header information is now stored in individual participant-level output JSON files instead of single-participant CSVs. At the end of the pipeline run, the information in these JSON files can be consolidated using the qap_jsons_to_csv.py script.
• Visualization graphs & reports are now generated using the qap_jsons_to_csv.py script upon completion of the pipeline run.
• Consolidated the data configuration file (participant list) generator scripts into one multi-purpose script (qap_sublist_generator.py), which supports BIDS directory format and AWS S3 bucket file path links.
• The pipeline configuration YAML file parameter names have been updated to be clearer.
• Introduction of the qap_check_output_csv.py script, which quickly compares the output CSV file against your original data configuration YAML file, then lists which participant-session-scans are missing in the final output and creates a new data configuration file with these scans for a convenient re-run.
• Users can now select to have zeros removed from anatomical scans prior to processing via the pipeline configuration file with the “exclude_zeros” flag. This is useful if a large number of zeros have been introduced to anatomical scans during de-facing and de-earing of images for privacy compliance, which can skew the QAP metric results.
• Improved information & error reporting.
• Fixed a bug where not all participants listed in the data configuration file would be run.
• Fixed several bugs that were causing report/PDF generation to crash or fail to complete.

Release 1.0.0

This is the initial release of the Preprocessed Connectome Project's Quality Assessment Protocol. This includes a collection of quality assessment metrics from the neuroimaging literature. These metrics are meant to be applied to raw structural and functional neuroimaging datasets.