mrQA 0.1.6

mrQA suite of tools offering automatic evaluation of protocol compliance

Quickstart

mrQA suite of tools offering

• automatic evaluation of protocol compliance

To use mrQA in a project:

import  mrQA

The most important methods for checking protocol compliance is mrQA.project.check_compliance. It calls all the required functions.

• To infer the most frequent values for each acquisition parameter

• Aggregate the non-compliance information to generate an HTML report

First of all, you have to import the relevant modules and classes:

from MRdataset import import_dataset
from mrQA import check_compliance

Given a dataset of MR images, (e.g. DICOM images), we create MRdataset.base.Project object. This can be achieved simply by MRdataset.import_dataset method, which requires a valid folder path. For details on MRdataset, please see its documentation.

data_root = '/home/user/datasets/ABCD'
output_dir = '/home/user/MR_reports/'
dataset = import_dataset(data_root=data_root,
                         style='xnat',
                         name='ABCD')

check_compliance(dataset=dataset, output_dir=output_dir)

And that’s it! Please note some important points:

• It will generate a corresponding HTML file in the output_dir which contains the complete report.

• style denotes the specific format of neuroimaging dataset. For example, use xnat for DICOM datasets and bids for BIDS datasets

• name is an identifier which can be used to reload the the cached files later.If no name is specified, it uses a random identifier.

History

0.1.0 (2022-05-20)

• First release on PyPI.