Module Detail Information

Name:DTIFIT
Type: Module
Short URL:
http://bit.ly/1AtBaYd
Description:DTIFIT DTIFIT fits a diffusion tensor model at each voxel. You would typically run dtifit on data that has been pre-processed and eddy current corrected. Note that dtifit is not necessary in order to use the probabilistic tractography (which depends on the output of BEDPOSTX not DTIFIT). 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 DTIFIT. Input: You can specify an input directory containing all the required files with standardized filenames, or alternatively you can specify input files manually by turning on the specify input files manually switch. If an input directory is specified then all files must be named as shown in parentheses below. If input files are specified manually they can have any filename. Required files are: Diffusion weighted data (data): A 4D series of data volumes. This will include diffusion-weighted volumes and volume(s) with no diffusion weighting. BET binary brain mask (nodif_brain_mask): A single binarised volume in diffusion space containing ones inside the brain and zeroes outside the brain. Output basename: User specifies a basename that will be used to name the outputs of dtifit. If the directory input option is used then the basename will be dti Gradient directions (bvecs): An ASCII 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 the input data series. 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 are normalised to unit length within the dtifit code. For volumes in which there was no diffusion weighting, the entry should still be present, although the direction of the vector does not matter! b values (bvals): An ASCII text file containing a list of b values 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 file. The format is b_1 b_2 b_3 ... b_n Outputs of dtifit _V1 - 1st eigenvector _V2 - 2nd eigenvector _V3 - 3rd eigenvector _L1 - 1st eigenvalue _L2 - 2nd eigenvalue _L3 - 3rd eigenvalue _MD - mean diffusivity _FA - fractional anisotropy _MO - mode of the anisotropy (oblate ~ -1; isotropic ~ 0; prolate ~ 1) _S0 - raw T2 signal with no diffusion weighting
Executable:
/dtifit
Input Parameters:
 - DTI data file
 - output
 - mask
 - bvecs
 - bvals
 - verbose
 - small brain area
Output Parameters:
File size:15.53 KB
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