def get_dti_streamlines(data_container,
random_seeds=False,
seeds_count=30000,
seeds_per_voxel=False,
step_width=1.0,
max_angle=30.0,
fa_threshold=0.15):
"""
Tracks and returns CSD Streamlines for the given DataContainer.
Parameters
----------
data_container
The DataContainer we would like to track streamlines on
random_seeds
A boolean indicating whether we would like to use random seeds
seeds_count
If we use random seeds, this specifies the seed count
seeds_per_voxel
If True, the seed count is specified per voxel
step_width
The step width used while tracking
fa_threshold
The FA threshold to use to stop tracking
max_angle
The maximum allowed angle between incoming and outgoing angle, float between 0.0 and 90.0 deg
Returns
-------
Streamlines
A list of Streamlines
"""
seeds = _get_seeds(data_container, random_seeds, seeds_count,
seeds_per_voxel)
dti_fit = TensorModel(data_container.gtab).fit(
data_container.dwi, mask=data_container.binary_mask)
dti_fit_odf = dti_fit.odf(sphere=default_sphere)
direction_getter = DeterministicMaximumDirectionGetter.from_pmf(
dti_fit_odf, max_angle=max_angle, sphere=default_sphere)
classifier = ThresholdStoppingCriterion(dti_fit.fa, fa_threshold)
streamlines_generator = LocalTracking(direction_getter,
classifier,
seeds,
data_container.aff,
step_size=step_width)
streamlines = Streamlines(streamlines_generator)
return streamlines
