Fmridenoise

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 the 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.

In version 0.2.0 we added several improvements:

* refactoring (breaking change) of console interface
* support for datasets containing runs
* new report layout
* new docker build
* better BIDS intergration
* refactoring of nipype based dataflow. Switch from maping nodes on list of elements to joins
* refactor of most internal components of fmridenoise
* separation of denoising and smooting step

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 the 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.

In version 0.1.1 we added several improvements:
- adapting the tool to work with the newest confounds regressors output from fMRIPrep (version 1.4.0 & 1.4.1),
- support for parallel computing (with --MultiProc flag),
- support for ICA-AROMA,
- identifying subjects to exclude due to high motion (according to recommendations from Parkes et al, 2018),
- new FC quality measures (distance-dependence, tDOF-loss),
- new plots (bar plots for quality measures with and without high motion subjects, motion summary swarm plots),
- updated aCompCor pipeline (with mean timeseries from PCs components calculated separately for WM and CSF as generated with fMRIPrep vesion 1.4.0 & 1.4.1),
- descriptions for each pipeline,
- smoothing,
- selecting specific subjects/sessions/tasks
- summary HTML report.

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 the 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.

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 the 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.

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 the 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.

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 the 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.