Note

This page is a reference documentation. It only explains the function signature, and not how to use it. Please refer to the user guide for the big picture.

brainprep.workflow.brainprep_group_quality_assurance

brainprep.workflow.brainprep_group_quality_assurance(modalities, output_dir, keep_intermediate=False)[source]

Group-level quality assurance pre-processing.

Summarizes the generated metrics [1] and applies the following quality control:

  1. Generate TSV tables of Image Quality Metrics (IQMs) generated by MRIQC.

  2. Generate TSV tables of quality assurance metrics for different modalities.

  3. Apply threshold-based quality checks on the selected quality metrics.

  4. Generate a histogram showing the distribution of these quality metrics.

The following quality metrics are considered:

  • TODO

Parameters:
modalities: list[str]

The modalities in the current study.

output_dirDirectory

Directory where the quality assurance related outputs will be saved (i.e., the root of your dataset).

keep_intermediatebool
If True, retains intermediate results (no effect on this workflow).

Default False.

Returns:
Bunch

A dictionary-like object containing:

  • iqm_files : list[File] — paths to the selected set o group-level uncorrelated Image Quality Metrics (IQMs).

Notes

This workflow assumes the subject-level analyses have already been performed.

References

Examples

>>> from brainprep.config import Config
>>> from brainprep.reporting import RSTReport
>>> from brainprep.workflow import brainprep_group_quality_assurance
>>>
>>> with Config(dryrun=True, verbose=False):
...     report = RSTReport()
...     outputs = brainprep_group_quality_assurance(
...         modalities=["T1w"],
...         output_dir="/tmp/dataset/derivatives",
...     )
>>> outputs
Bunch(
    iqm_files: [PosixPath('...')]
)

Examples using brainprep.workflow.brainprep_group_quality_assurance

Quality Assurance

Quality Assurance