jdkent / fmridenoise

Tool for automatic denoising, denoising strategies comparison, and functional connectivity data quality control.

fMRIDenoise - automated denoising, denoising strategies comparison, and functional connectivity data quality control.

Tool for automatic denoising, denoising strategies comparisons, and functional connectivity data quality control. The goal of fMRIDenoise is to provide an objective way to select best-performing denoising strategy given the data. FMRIDenoise is designed to work directly on fMRIPrep-preprocessed datasets and data in BIDS standard. We believe that the tool can make the selection of the denoising strategy more objective and also help researchers to obtain FC quality control metrics with almost no effort.

Problem

Solution

Installation

Run:

python setup.py install (--user)

Currently there is no fmridenoise version available in PyPi.

Execution

python -m fmridenoise

positional arguments:
bids_dir              Path do preprocessed BIDS dataset.

optional arguments:
-h, --help            show this help message and exit
-g, --debug           Run fmridenoise in debug mode
--graph GRAPH         Create workflow graph at given path
-d DERIVATIVES [DERIVATIVES ...], --derivatives DERIVATIVES [DERIVATIVES ...]
                        Name (or list) of derivatives for which fmridenoise
                        should be run. By default workflow looks for fmriprep
                        dataset.
-sub SUBJECTS [SUBJECTS ...], --subjects SUBJECTS [SUBJECTS ...]
                        List of subjects
-ses SESSIONS [SESSIONS ...], --sessions SESSIONS [SESSIONS ...]
                        List of session numbers
-t TASKS [TASKS ...], --tasks TASKS [TASKS ...]
                        List of tasks names
-p PIPELINES [PIPELINES ...], --pipelines PIPELINES [PIPELINES ...]
                        Name of pipelines used for denoising
--high_pass HIGH_PASS
                        High pass filter value
--low_pass LOW_PASS   Low pass filter value
--MultiProc           EXPERIMENTAL: Run script on multiple processors,
                        default False
--profiler PROFILER   Run profiler along workflow execution to estimate
                        resources usage PROFILER is path to output log file.
--dry                 Perform everything but do not run workflow