Bedpost stands for Bayesian Estimation of Diffusion Parameters obtained using sampling
techniques. Bedpost runs Markov Chain Monte Carlo sampling to build up distributions on diffusion parameters at each voxel. It creates all the
files neccessary for running probabilistic tractography. For an overview of
the modelling carried out within Bedpost see the appendix.
Bedpost takes about 24 hours to run but can easily be parallelised if multiple
processors are available.
To call the FDT GUI, either run Fdt, or run fsl and press the
FDT button. Use the top left drop down menu to select Bedpost.
Input directory: Use the browse button to select and input directory.
That directory must contain the following files:
- data: A 4-dimensional series of data volumes. This will
include diffusion-weighted volumes and volume(s) with no diffusion weighting.
- nodif: 3D volume with no diffusion weighting
- nodif_brain_mask: 3D binary brain mask volume derived
from running bet on nodif
- bvecs A text file containing a list
of gradient directions applied during diffusion weighted volumes. The
order of entries in this file must match the order of volumes in data.
The format is
x_1 x_2 x_3 ... x_n
y_1 y_2 y_3 ... y_n
z_1 z_2 z_3 ... z_n
Vectors should be normalised. For volumes in which there was no
diffusion weighting, the entry should still be present, although the
direction of the vector does not matter!
- bvals A text file containing a list of bvalues applied during
each volume acquisition. The order of entries in this file must match the
order of volumes in the input data and entries in the gradient directions text
The format is
b_1 b_2 b_3 ... b_n
The order of bvals must match the order of data.
Outputs of Bedpost
Bedpost creates a new directory at the same level as the input directory
called .bedpost which contains all the files you need for probabilistic
tractography. Highlights are: