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 necessary for running probabilistic tractography. For an overview of
the modelling carried out within Bedpost see the Bedpost now allows to model crossing fibres within each voxel on the brain. Crucially, Bedpost only models crossing fibres in voxels where the data support crossing fibres. For details on the model used in this case, see Behrens et al, NeuroImage 2007, 34:144-55.
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 an input directory.
That directory must contain the following files:
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
For volumes in which there was no diffusion weighting, the entry should still be present, although the
direction of the vector does not matter!
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 <indir>.bedpost which contains all the files you need for probabilistic
tractography. Highlights are (<i> indicates the i-th fibre. It ranges from 1 to the maximum number of fibres set in the advanced options.):
Advanced options
You may change some options before running Bedpost, depending on the questions you want to ask or the quality of your diffusion data. The default values of these parameters are the ones used in the corresponding paper (Behrens et al, NeuroImage 2007).
command line utility