AFNI Diffusion Tensor Fitting (3dDWItoDT)¶
Library: AFNI | Docker Image: brainlife/afni
Function¶
Fits a diffusion tensor model to DWI data using linear or nonlinear methods, outputting tensor components, eigenvalues, and eigenvectors.
Modality: 4D diffusion-weighted dataset with gradient vector file.
Typical Use: Computing diffusion tensor and derived scalar maps (FA, MD) from DWI data in AFNI workflows.
Key Parameters¶
-prefix (output prefix), -mask (brain mask), -eigs (output eigenvalues/eigenvectors), -nonlinear, -automask
Key Points¶
Supports linear (default) and nonlinear fitting. Use -eigs for eigenvalue/eigenvector output required by 3dTrackID. Gradient file needs 3 columns per direction.
Inputs¶
| Name | Type | Required | Label | Flag |
|---|---|---|---|---|
prefix |
string |
Yes | Output dataset prefix | -prefix |
gradient_file |
File |
Yes | Gradient vector file (3 columns per direction) | |
input |
File |
Yes | Input 4D DWI dataset | |
mask |
File |
No | Brain mask dataset | -mask |
automask |
boolean |
No | Automatically compute brain mask from data | -automask |
eigs |
boolean |
No | Output eigenvalues and eigenvectors | -eigs |
debug_briks |
boolean |
No | Output additional debugging volumes | -debug_briks |
cumulative_wts |
boolean |
No | Output cumulative weights | -cumulative_wts |
nonlinear |
boolean |
No | Compute nonlinear tensor fit | -nonlinear |
linear |
boolean |
No | Compute linear tensor fit (default) | -linear |
sep_dsets |
boolean |
No | Output separate datasets for each DTI parameter (FA, MD, V1, etc.) | -sep_dsets |
reweight |
boolean |
No | Reweight the data | -reweight |
max_iter |
int |
No | Maximum number of iterations for nonlinear fit | -max_iter |
max_iter_rw |
int |
No | Maximum iterations for reweight | -max_iter_rw |
opt |
enum |
No | Optimization method for nonlinear | -opt |
Accepted Input Extensions¶
- input:
.nii,.nii.gz,.HEAD - gradient_file:
.1D,.txt
Outputs¶
| Name | Type | Glob Pattern |
|---|---|---|
tensor |
File[] |
$(inputs.prefix)*+orig.HEAD, $(inputs.prefix)*+orig.BRIK, $(inputs.prefix)*+orig.BRIK.gz, $(inputs.prefix)*+tlrc.HEAD, $(inputs.prefix)*+tlrc.BRIK, $(inputs.prefix)*+tlrc.BRIK.gz |
log |
File |
$(inputs.prefix).log |
Output Extensions¶
- tensor:
.HEAD,.nii,.nii.gz
Docker Tags¶
Available versions: latest, 16.3.0
Categories¶
- Diffusion MRI > AFNI > Tensor Fitting