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FSL Component Regression Filter (fsl_regfilt)

Library: FSL | Docker Image: brainlife/fsl

Function

Removes nuisance components from 4D fMRI data by regressing out specified columns from a design or mixing matrix.

Modality: 4D fMRI NIfTI time series with associated ICA mixing matrix.

Typical Use: Removing ICA-identified noise components from fMRI data, often used with FIX or manual classification.

Key Parameters

-i (input 4D), -d (design/mixing matrix), -o (output), -f (component indices to remove)

Key Points

Typically used with MELODIC output. Removes ICA components classified as noise. Component indices are comma-separated or ranges.

Inputs

Name Type Required Label Flag
input File Yes Input 4D data file -i
design File Yes Design matrix (e.g., MELODIC mixing matrix) -d
output string Yes Output filename -o
filter string Yes Component indices to filter out (comma-separated, 1-indexed) -f
aggressive boolean No Use aggressive (full variance) filtering -a
freq_filter boolean No Frequency-based filtering --freq
freq_ic File No Frequency IC file for frequency-based filtering --freq_ic
verbose boolean No Verbose output -v
mask File No Brain mask -m

Accepted Input Extensions

  • input: .nii, .nii.gz
  • design: .txt, .mat

Outputs

Name Type Glob Pattern
filtered_data File $(inputs.output).nii.gz, $(inputs.output).nii, $(inputs.output)
log File fsl_regfilt.log

Output Extensions

  • output: .nii, .nii.gz

Docker Tags

Available versions: latest, 6.0.4-patched2, 6.0.4-patched, 6.0.4, 6.0.4-xenial, 5.0.11, 6.0.0, 6.0.1, 5.0.9

Categories

  • Functional MRI > FSL > ICA/Denoising

Documentation

Official Documentation