mia_processes.bricks.preprocess.mrtrix package

Mrtrix processes.

Submodules

mia_processes.bricks.preprocess.mrtrix.processes module

The mrtrix (mrtrix3) preprocess library of the mia_processes package.

The purpose of this module is to customise the main mrtrix preprocessing bricks provided by nipype and to correct some things that do not work directly in populse_mia.

Contains:
Class:

  • ConstrainedSphericalDeconvolution

  • DWIBiasCorrect

  • DWIBrainMask

  • DWICat

  • DWIDenoise

  • DWIExtract

  • DWIPreproc

  • EditingTrack

  • FitTensor

  • FilteringTrack

  • Generate5ttfsl

  • Generate5tt2gmwmi

  • MRCat

  • MRConvert

  • MRDeGibbs

  • MRGridRegrid

  • MRMath

  • MRTransform

  • MTNormalise

  • ResponseSDDhollander

  • ResponseSDTournier

  • SphericalHarmonicExtraction

  • TensorMetrics

  • Tractography

  • TransformFSLConvert

class mia_processes.bricks.preprocess.mrtrix.processes.ConstrainedSphericalDeconvolution[source]

Bases: ProcessMIA

Estimate fibre orientation distributions from diffusion data using spherical deconvolution (dwi2fod command)

Please, see the complete documentation for the ConstrainedSphericalDeconvolution brick in the mia_processes website

Note

  • Type ‘ConstrainedSphericalDeconvolution.help()’ for a full description of this process parameters.

  • Type ‘<ConstrainedSphericalDeconvolution>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<ConstrainedSphericalDeconvolution>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.DWIBiasCorrect[source]

Bases: ProcessMIA

Perform B1 field inhomogeneity correction for a DWI volume series. (dwibiascorrect command)

Please, see the complete documentation for the DWIBiasCorrect brick in the mia_processes website

Note

  • Type ‘DWIBiasCorrect.help()’ for a full description of this process parameters.

  • Type ‘<DWIBiasCorrect>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<DWIBiasCorrect>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.DWIBrainMask[source]

Bases: ProcessMIA

Generates a whole brain mask from a DWI image. (dwi2mask command)

Please, see the complete documentation for the DWIBrainMask brick in the mia_processes website

Note

  • Type ‘DWIBrainMask.help()’ for a full description of this process parameters.

  • Type ‘<DWIBrainMask>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<DWIBrainMask>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.DWICat[source]

Bases: ProcessMIA

Concatenating multiple DWI series with intensity scaling (dwicat command)

Please, see the complete documentation for the DWICat brick in the mia_processes website

Note

  • Type ‘DWICat.help()’ for a full description of this process parameters.

  • Type ‘<DWICat>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<DWICat>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.DWIDenoise[source]

Bases: ProcessMIA

Denoise DWI data and estimate the noise level based on the optimal threshold for PCA. (dwi denoise command)

Please, see the complete documentation for the DWIDenoise brick in the mia_processes website

Note

  • Type ‘DWIDenoise.help()’ for a full description of this process parameters.

  • Type ‘<DWIDenoise>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<DWIDenoise>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.DWIExtract[source]

Bases: ProcessMIA

Extract diffusion-weighted volumes, b=0 volumes, or certain shells from a DWI dataset (dwiextract command)

Please, see the complete documentation for the DWIExtract brick in the mia_processes website

Note

  • Type ‘DWIExtract.help()’ for a full description of this process parameters.

  • Type ‘<DWIExtract>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<DWIExtract>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.DWIPreproc[source]

Bases: ProcessMIA

Perform diffusion image pre-processing using FSL’s eddy tool; including inhomogeneity distortion correction using FSL’s topup tool if possible (dwifslpreproc command)

Please, see the complete documentation for the DWIPreproc brick in the mia_processes website

Note

  • Type ‘DWIPreproc.help()’ for a full description of this process parameters.

  • Type ‘<DWIPreproc>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<DWIPreproc>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.EditingTrack[source]

Bases: ProcessMIA

Perform various editing operations on track files. (tckedit command)

Please, see the complete documentation for the EditingTrack brick in the mia_processes website

Note

  • Type ‘EditingTrack.help()’ for a full description of this process parameters.

  • Type ‘<EditingTrack>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<EditingTrack>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.FilteringTrack[source]

Bases: ProcessMIA

Filter a whole-brain fibre-tracking data set such that the streamline densities match the FOD lobe integrals. (tcksift command)

Please, see the complete documentation for the FilteringTrack brick in the mia_processes website

Note

  • Type ‘FilteringTrack.help()’ for a full description of this process parameters.

  • Type ‘<FilteringTrack>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<FilteringTrack>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.FitTensor[source]

Bases: ProcessMIA

Convert diffusion-weighted images to tensor images. (dwi2tensor command)

Please, see the complete documentation for the FitTensor brick in the mia_processes website

Note

  • Type ‘FitTensor.help()’ for a full description of this process parameters.

  • Type ‘<FitTensor>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<FitTensor>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.Generate5tt2gmwmi[source]

Bases: ProcessMIA

Generate a mask image appropriate for seeding streamlines on the grey matter-white matter interface (5tt2gmwmi command)

Please, see the complete documentation for the Generate5tt2gmwmi brick in the mia_processes website

Note

  • Type ‘Generate5tt2gmwmi.help()’ for a full description of this process parameters.

  • Type ‘<Generate5tt2gmwmi>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<Generate5tt2gmwmi>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.Generate5ttfsl[source]

Bases: ProcessMIA

Generate a 5TT image suitable for ACT using the selected algorithm. (5ttgen command)

Please, see the complete documentation for the Generate5ttfsl brick in the mia_processes website

Note

  • Type ‘Generate5ttfsl.help()’ for a full description of this process parameters.

  • Type ‘<Generate5ttfsl>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<Generate5ttfsl>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.MRCat[source]

Bases: ProcessMIA

Concatenate several images into one

Please, see the complete documentation for the MRCat brick in the mia_processes website

Note

  • Type ‘MRCat.help()’ for a full description of this process parameters.

  • Type ‘<MRCat>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<MRCat>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.MRConvert[source]

Bases: ProcessMIA

Perform conversion between different file types and optionally extract a subset of the input image. (mrconvert command)

Please, see the complete documentation for the MRConvert brick in the mia_processes website

Note

  • Type ‘MRConvert.help()’ for a full description of this process parameters.

  • Type ‘<MRConvert>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<MRConvert>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.MRDeGibbs[source]

Bases: ProcessMIA

Remove Gibbs ringing artifacts. (mrdegibbs command)

Please, see the complete documentation for the MRDeGibbs brick in the mia_processes website

Note

  • Type ‘MRDeGibbs.help()’ for a full description of this process parameters.

  • Type ‘<MRDeGibbs>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<MRDeGibbs>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.MRGridRegrid[source]

Bases: ProcessMIA

Modify the grid of an image by performing changes of the voxel grid that require interpolation of the image (mrgrid regrid command)

Please, see the complete documentation for the MRGridRegrid brick in the mia_processes website

Note

  • Type ‘MRGridRegrid.help()’ for a full description of this process parameters.

  • Type ‘<MRGridRegrid>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<MRGridRegrid>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.MRMath[source]

Bases: ProcessMIA

Compute summary statistic on image intensities along a specified axis of a single image (mrmath command)

Please, see the complete documentation for the MRMath brick in the mia_processes website

Note

  • Type ‘MRMath.help()’ for a full description of this process parameters.

  • Type ‘<MRMath>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<MRMath>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.MRTransform[source]

Bases: ProcessMIA

Apply spatial transformations or reslice images (mrtransform command)

Please, see the complete documentation for the MRTransform brick in the mia_processes website

Note

  • Type ‘MRTransform.help()’ for a full description of this process parameters.

  • Type ‘<MRTransform>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<MRTransform>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.MTNormalise[source]

Bases: ProcessMIA

Multi-tissue informed log-domain intensity normalisation. (mtnormalise command)

Please, see the complete documentation for the MTNormalise brick in the mia_processes website

Note

  • Type ‘MTNormalise.help()’ for a full description of this process parameters.

  • Type ‘<MTNormalise>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<MTNormalise>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.ResponseSDDhollander[source]

Bases: ProcessMIA

Estimate response function(s) for spherical deconvolution using the Dhollander algorithm (dwi2response command)

Please, see the complete documentation for the ResponseSDDhollander brick in the mia_processes website

Note

  • Type ‘ResponseSDDhollander.help()’ for a full description of this process parameters.

  • Type ‘<ResponseSDDhollander>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<ResponseSDDhollander>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.ResponseSDTournier[source]

Bases: ProcessMIA

Estimate response function(s) for spherical deconvolution using the Tournier algorithm (dwi2response command)

Please, see the complete documentation for the ResponseSDTournier brick in the mia_processes website

Note

  • Type ‘ResponseSDTournier.help()’ for a full description of this process parameters.

  • Type ‘<ResponseSDTournier>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<ResponseSDTournier>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.SphericalHarmonicExtraction[source]

Bases: ProcessMIA

Extract the peaks of a spherical harmonic function in each voxel. (sh2peaks command)

Please, see the complete documentation for the SphericalHarmonicExtraction brick in the mia_processes website

Note

  • Type ‘SphericalHarmonicExtraction.help()’ for a full description of this process parameters.

  • Type ‘<SphericalHarmonicExtraction>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<SphericalHarmonicExtraction>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.TensorMetrics[source]

Bases: ProcessMIA

Compute metrics from tensors (tensor2metric command)

Please, see the complete documentation for the TensorMetrics brick in the mia_processes website

Note

  • Type ‘TensorMetrics.help()’ for a full description of this process parameters.

  • Type ‘<TensorMetrics>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<TensorMetrics>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.Tractography[source]

Bases: ProcessMIA

Performs streamlines tractography after selecting the appropriate algorithm. (tckgen command)

Please, see the complete documentation for the Tractography brick in the mia_processes website

Note

  • Type ‘Tractography.help()’ for a full description of this process parameters.

  • Type ‘<Tractography>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<Tractography>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.

class mia_processes.bricks.preprocess.mrtrix.processes.TransformFSLConvert[source]

Bases: ProcessMIA

Perform conversion between FSL’s transformation matrix format to mrtrix3’s. (transformconvert command)

Please, see the complete documentation for the TransformFSLConvert brick in the mia_processes website

Note

  • Type ‘TransformFSLConvert.help()’ for a full description of this process parameters.

  • Type ‘<TransformFSLConvert>.get_input_spec()’ for a full description of this process input trait types.

  • Type ‘<TransformFSLConvert>.get_output_spec()’ for a full description of this process output trait types.

__init__()[source]

Dedicated to the attributes initialisation/instantiation. The input and output plugs are defined here. The special ‘self.requirement’ attribute (optional) is used to define the third-party products necessary for the running of the brick.

list_outputs(is_plugged=None, iteration=False)[source]

Dedicated to the initialisation step of the brick. The main objective of this method is to produce the outputs of the bricks (self.outputs) and the associated tags (self.inheritance_dic), if defined here. In order not to include an output in the database, this output must be a value of the optional key ‘notInDb’ of the self.outputs dictionary. To work properly this method must return self.make_initResult() object.

Parameters:

  • is_plugged – the state, linked or not, of the plugs.

  • iteration – the state, iterative or not, of the process.

Returns:

a dictionary with requirement, outputs and inheritance_dict.

run_process_mia()[source]

Dedicated to the process launch step of the brick.