import os
import os.path as op
import numpy as np
import nibabel as nib
from dipy.reconst import fwdti
import AFQ.utils.models as ut
__all__ = ["fit_fwdti"]
def _fit(data, gtab, mask):
fwmodel = fwdti.FreeWaterTensorModel(gtab)
fwfit = fwmodel.fit(data, mask=mask)
return fwfit
[docs]def fit_fwdti(data_files, bval_files, bvec_files, mask=None, out_dir=None,
b0_threshold=50):
"""
Fit the free water DTI model [1]_, save files with derived maps
Parameters
----------
data_files : str or list
Files containing DWI data. If this is a str, that's the full path to a
single file. If it's a list, each entry is a full path.
bval_files : str or list
Equivalent to `data_files`.
bvec_files : str or list
Equivalent to `data_files`.
mask : ndarray, optional
Binary mask, set to True or 1 in voxels to be processed.
Default: Process all voxels.
out_dir : str, optional
A full path to a directory to store the maps that get computed.
Default: maps get stored in the same directory as the last DWI file
in `data_files`.
b0_threshold : float
Returns
-------
file_paths : a dict with the derived maps that were computed and full-paths
to the files containing these maps.
Note
----
..[1] R. Neto Henriques, A. Rokem, E. Garyfallidis, S. St-Jean, E.T.
Peterson, M. Correia (2017). [Re] Optimization of a free water
elimination two-compartment model for diffusion tensor imaging.
*ReScience*
"""
img, data, gtab, mask = ut.prepare_data(data_files, bval_files,
bvec_files, mask=mask,
b0_threshold=b0_threshold)
fwfit = _fit(data, gtab, mask)
FA = fwfit.fa
MD = fwfit.md
AD = fwfit.ad
RD = fwfit.rd
fwvf = fwfit.f
params = fwfit.model_params
maps = [FA, MD, AD, RD, fwvf, params]
names = ['FA', 'MD', 'AD', 'RD', 'FWVF', 'params']
if out_dir is None:
if isinstance(data_files, list):
out_dir = op.join(op.split(data_files[0])[0], 'fwdti')
else:
out_dir = op.join(op.split(data_files)[0], 'fwdti')
if not op.exists(out_dir):
os.makedirs(out_dir)
aff = img.affine
file_paths = {}
for m, n in zip(maps, names):
file_paths[n] = op.join(out_dir, 'fwdti_%s.nii.gz' % n)
nib.save(nib.Nifti1Image(m, aff), file_paths[n])
return file_paths
