nifreeze.model.dmri module¶
- class nifreeze.model.dmri.AverageDWIModel(self, dataset: nifreeze.data.dmri.DWI, stat: str = 'median', th_low: float = 100.0, th_high: float = 100.0, detrend: bool = False, **kwargs)[source]¶
Bases:
ExpectationModel
A trivial model that returns an average DWI volume.
Implement object initialization.
- Parameters:
dataset (
DWI
) – Reference to a DWI object.stat (
str
, optional) – Whether the summary statistic to apply is"mean"
or"median"
.th_low (
float
, optional) – A lower bound for the b-value corresponding to the diffusion weighted images that will be averaged.th_high (
float
, optional) – An upper bound for the b-value corresponding to the diffusion weighted images that will be averaged.detrend (
bool
, optional) – Whether the overall distribution of each diffusion weighted image will be standardized and centered around thesrc.nifreeze.model.base.DEFAULT_CLIP_PERCENTILE
percentile.
- class nifreeze.model.dmri.BaseDWIModel(self, dataset: nifreeze.data.dmri.DWI, **kwargs)[source]¶
Bases:
BaseModel
Interface and default methods for DWI models.
Initialization.
- Parameters:
dataset (
DWI
) – Reference to a DWI object.
- class nifreeze.model.dmri.DKIModel(self, dataset: nifreeze.data.dmri.DWI, **kwargs)[source]¶
Bases:
BaseDWIModel
A wrapper of
dipy.reconst.dki.DiffusionKurtosisModel
.Initialization.
- Parameters:
dataset (
DWI
) – Reference to a DWI object.
- class nifreeze.model.dmri.DTIModel(self, dataset: nifreeze.data.dmri.DWI, **kwargs)[source]¶
Bases:
BaseDWIModel
A wrapper of
dipy.reconst.dti.TensorModel
.Initialization.
- Parameters:
dataset (
DWI
) – Reference to a DWI object.
- class nifreeze.model.dmri.GPModel(self, dataset: nifreeze.data.dmri.DWI, **kwargs)[source]¶
Bases:
BaseDWIModel
A wrapper of
GaussianProcessModel
.Initialization.
- Parameters:
dataset (
DWI
) – Reference to a DWI object.