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Denoiser: A nuisance regression tool for fMRI BOLD data

Denoiser is a tool for removing sources of noise from and performing temporal filtering of functional MRI data. It also provides visualization of the content of nuisance signals (including motion information, if provided), allowing the user to get a quick sense of data quality before and after noise removal.

Denoiser acts on 4D fMRI data (takes either a nifti file path or an already loaded nibabel object as input). Nuisance signal removal and temporal filtering are performed on a voxel-wise level, and a 'cleaned' 4D Nifti file (_NR file)/ nibabel object are created as outputs.

The specific noise signals to be removed are specified by the user (contained in a tsv file). This tool should be used only after BOLD data are minimally preprocessed (for example, after preprocessing the data using fmriprep, which creates a .tsv file containing nuisance signals).

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Nuisance removal tool for fMRI data

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  • Python 85.2%
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