cmp.stages.diffusion.tracking module
Tracking methods and workflows of the diffusion stage.
- class cmp.stages.diffusion.tracking.DipyTrackingConfig[source]
Bases:
traits.has_traits.HasTraits
Class used to store Dipy diffusion reconstruction sub-workflow configuration parameters.
- imaging_model
Diffusion imaging model (For example ‘DTI’)
- Type
traits.Str
- tracking_mode
Type of local tractography algorithm (Can be “Deterministic” or “Probabilistic”)
- Type
traits.Str
- SD
If
True
, inputs are coming from Constrained Spherical Deconvolution reconstruction- Type
traits.Bool
- number_of_seeds
Number of seeds (Default: 1000)
- Type
traits.Int
- seed_density
Number of seeds to place along each direction where a density of 2 is the same as [2, 2, 2] and will result in a total of 8 seeds per voxel (Default: 1.0)
- Type
traits.Float
- fa_thresh
Fractional Anisotropy (FA) threshold (Default: 0.2)
- Type
traits.Float
- step_size
Tractography algorithm step size (Default: 0.5)
- Type
traits.traits.Float
- max_angle
Maximum streamline angle allowed (Default: 25.0)
- Type
traits.Float
- sh_order
Order used for Constrained Spherical Deconvolution reconstruction (Default: 8)
- Type
traits.Int
- use_act
Use FAST for partial volume estimation and Anatomically-Constrained Tractography (ACT) tissue classifier (Default: False)
- Type
traits.Bool
- seed_from_gmwmi
Seed from Grey Matter / White Matter interface (requires Anatomically-Constrained Tractography (ACT)) (Default: False)
- Type
traits.Bool
- class cmp.stages.diffusion.tracking.MRtrixTrackingConfig[source]
Bases:
traits.has_traits.HasTraits
Class used to store Dipy diffusion reconstruction sub-workflow configuration parameters.
- tracking_mode
Type of local tractography algorithm (Can be “Deterministic” or “Probabilistic”)
- Type
traits.Str
- SD
If
True
, inputs are coming from Constrained Spherical Deconvolution reconstruction- Type
traits.Bool
- desired_number_of_tracks
Desired number of output streamlines in the tractogram (Default: 1M)
- Type
traits.Int
- curvature = Float
Maximum streamline curvature (Default: 2.0)
- min_length = Float
Minimal streamline length (Default: 5)
- max_length = Float
Maximal streamline length (Default: 500)
- angle
Maximum streamline angle allowed (Default: 45.0)
- Type
traits.Float
- cutoff_value
Cut-off value to terminate streamline (Default: 0.05)
- Type
traits.Float
- use_act
Use
5ttgen
for brain tissue types estimation and Anatomically-Constrained Tractography (ACT) tissue classifier (Default: False)- Type
traits.Bool
- seed_from_gmwmi
Seed from Grey Matter / White Matter interface (requires Anatomically-Constrained Tractography (ACT)) (Default: False)
- Type
traits.Bool
- crop_at_gmwmi
Crop streamline endpoints more precisely as they cross the GM-WM interface (requires Anatomically-Constrained Tractography (ACT)) (Default: True)
- Type
traits.Bool
- backtrack
Allow tracks to be truncated (requires Anatomically-Constrained Tractography (ACT)) (Default: True)
- Type
traits.Bool
- sift
Filter tractogram using mrtrix3 SIFT (Default: True)
- Type
traits.Bool
- cmp.stages.diffusion.tracking.create_dipy_tracking_flow(config)[source]
Create the tractography sub-workflow of the
DiffusionStage
using Dipy.- Parameters
config (DipyTrackingConfig) – Sub-workflow configuration object
- Returns
flow – Built tractography sub-workflow
- Return type
nipype.pipeline.engine.Workflow
- cmp.stages.diffusion.tracking.create_mrtrix_tracking_flow(config)[source]
Create the tractography sub-workflow of the
DiffusionStage
using MRtrix3.- Parameters
config (MRtrixTrackingConfig) – Sub-workflow configuration object
- Returns
flow – Built tractography sub-workflow
- Return type
nipype.pipeline.engine.Workflow