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Bayesian Estimation of Diffusion Parameters Obtained using Sampling Techniques (BEDPOSTX)

Library: FSL | Docker Image: brainlife/fsl

Function

Multi-step pipeline for Bayesian estimation of fiber orientation distributions. Internally runs multi-fiber MCMC sampling across all voxels with automatic convergence checking, supporting multiple crossing fibers per voxel.

Modality: Directory containing 4D DWI (data.nii.gz), b-values (bvals), b-vectors (bvecs), and brain mask (nodif_brain_mask.nii.gz).

Typical Use: Prerequisite for probabilistic tractography with probtrackx2.

Key Parameters

, -n (max fibers per voxel, default 3)

Key Points

Very computationally intensive (hours-days). GPU version (bedpostx_gpu) strongly recommended. Required before probtrackx2. Outputs fiber orientations and uncertainty estimates.

Inputs

Name Type Required Label Flag
data_dir Directory Yes Input data directory (must contain data, bvals, bvecs, nodif_brain_mask)
nfibres int No Number of fibres per voxel (default 3) -n
model int No Deconvolution model (1=monoexp, 2=multiexp, 3=zeppelin) -model
rician boolean No Use Rician noise modelling --rician

Outputs

Name Type Glob Pattern
output_directory Directory $(inputs.data_dir.basename).bedpostX
merged_samples File[] $(inputs.data_dir.basename).bedpostX/merged_*samples.nii.gz
log File bedpostx.log

Output Extensions

  • merged_samples: .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

  • Diffusion MRI > FSL > Tractography
  • Pipelines > FSL > Diffusion

Documentation

Official Documentation