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.quality_assurance.brainprep_quality_assurance

brainprep.workflow.quality_assurance.brainprep_quality_assurance(image_files, output_dir, keep_intermediate=False, **kwargs)

Subject level quality assurance pre-processing workflow for MRI images.

Applies MRIQC tool [1] with subject level default settings.

Parameters:

image_fileslist[File]

Path to the input image files of one subject.

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 (i.e., the workspace); useful for debugging. Default False.

**kwargsdict

entities: lsit[dict]

Dictionaries of parsed BIDS entities.

Returns:

Bunch

A dictionary-like object containing:

• iqm_files : list[File] — paths to the subject level Image Quality Metrics (IQMs).

Notes

This workflow assumes the input images are organized in BIDS.

References

[1]

Oscar Esteban, Daniel Birman, Marie Schaer, Oluwasanmi O. Koyejo, Russell A. Poldrack, and Krzysztof J. Gorgolewski. Mriqc: advancing the automatic prediction of image quality in mri from unseen sites. PLOS ONE, 12(9):e0184661, 2017.

Examples

>>> from brainprep.config import Config
>>> from brainprep.reporting import RSTReport
>>> from brainprep.workflow import brainprep_quality_assurance
>>>
>>> with Config(dryrun=True, verbose=False):
...     report = RSTReport()
...     outputs = brainprep_quality_assurance(
...         image_files=[
...             "/tmp/dataset/rawdata/sub-01/ses-01/anat/"
...             "sub-01_ses-01_run-01_T1w.nii.gz",
...             "/tmp/dataset/rawdata/sub-01/ses-01/dwi/"
...             "sub-01_ses-01_run-01_dwi.nii.gz",
...         ],
...         output_dir="/tmp/dataset/derivatives",
...     )
>>> outputs
Bunch(
    iqm_files: [PosixPath('...'), PosixPath('...')]
)