Postprocess module

PyMIALSRTK postprocessing functions.

It encompasses a High Resolution mask refinement and an N4 global bias field correction.

FilenamesGeneration

Link to code

Bases: nipype.interfaces.base.core.BaseInterface

Generates final filenames from outputs of super-resolution reconstruction.

Example

>>> from pymialsrtk.interfaces.postprocess import FilenamesGeneration
>>> filenamesGen = FilenamesGeneration()
>>> filenamesGen.inputs.sub_ses = 'sub-01'
>>> filenamesGen.inputs.stacks_order = [3,1,4]
>>> filenamesGen.inputs.sr_id = 3
>>> filenamesGen.inputs.use_manual_masks = False
>>> filenamesGen.run() # doctest: +SKIP

sr_id : an integer (int or long)

Super-Resolution id.

stacks_order : a list of items which are any value

List of stack run-id that specify the order of the stacks.

sub_ses : a unicode string

Subject and session BIDS identifier to construct output filename.

use_manual_masks : a boolean

Whether masks were computed or manually performed.

substitutions : a list of items which are any value

Output correspondance between old and new filenames.

FilenamesGeneration.m_substitutions = []

MialsrtkN4BiasFieldCorrection

Link to code

Bases: nipype.interfaces.base.core.BaseInterface

Runs the MIAL SRTK slice by slice N4 bias field correction module.

This tools implements the method proposed by Tustison et al. [1]_ slice by slice.

References

[1]	Tustison et al.; Medical Imaging, IEEE Transactions, 2010. (link to paper)

Example

>>> from pymialsrtk.interfaces.preprocess import MialsrtkSliceBySliceN4BiasFieldCorrection
>>> N4biasFieldCorr = MialsrtkSliceBySliceN4BiasFieldCorrection()
>>> N4biasFieldCorr.inputs.bids_dir = '/my_directory'
>>> N4biasFieldCorr.inputs.input_image = 'sub-01_acq-haste_run-1_SR.nii.gz'
>>> N4biasFieldCorr.inputs.input_mask = 'sub-01_acq-haste_run-1_mask.nii.gz'
>>> N4biasFieldCorr.run() # doctest: +SKIP

bids_dir : a directory name

BIDS root directory.

input_image : a pathlike object or string representing a file

Input image filename to be normalized.

input_mask : a pathlike object or string representing a file

Input mask filename.

out_fld_postfix : a unicode string

(Nipype default value: _gbcorrfield)

out_im_postfix : a unicode string

(Nipype default value: _gbcorr)

output_field : a pathlike object or string representing a file

Output bias field extracted from input image.

output_image : a pathlike object or string representing a file

Output corrected image.

MialsrtkRefineHRMaskByIntersection

Link to code

Bases: nipype.interfaces.base.core.BaseInterface

Runs the MIAL SRTK mask refinement module.

It uses the Simultaneous Truth And Performance Level Estimate (STAPLE) by Warfield et al. [1]_.

References

[1]	Warfield et al.; Medical Imaging, IEEE Transactions, 2004. (link to paper)

Example

>>> from pymialsrtk.interfaces.postprocess import MialsrtkRefineHRMaskByIntersection
>>> refMask = MialsrtkRefineHRMaskByIntersection()
>>> refMask.inputs.bids_dir = '/my_directory'
>>> refMask.inputs.input_images = ['sub-01_acq-haste_run-1_T2w.nii.gz','sub-01_acq-haste_run-2_T2w.nii.gz']
>>> refMask.inputs.input_masks = ['sub-01_acq-haste_run-1_mask.nii.gz','sub-01_acq-haste_run-2_mask.nii.gz']
>>> refMask.inputs.input_transforms = ['sub-01_acq-haste_run-1_transform.txt','sub-01_acq-haste_run-2_transform.nii.gz']
>>> refMask.inputs.input_sr = 'sr_image.nii.gz'
>>> refMask.run()  # doctest: +SKIP

bids_dir : a directory name

BIDS root directory.

input_sr : a pathlike object or string representing a file

SR image filename.

in_use_staple : a boolean

Use STAPLE for voting (default is True). If False, Majority voting is used instead. (Nipype default value: True)

input_images : a list of items which are a pathlike object or string representing a file

Image filenames used in SR reconstruction.

input_masks : a list of items which are a pathlike object or string representing a file

Mask filenames.

input_rad_dilatation : an integer (int or long)

Radius of the structuring element (ball). (Nipype default value: 1)

input_transforms : a list of items which are a pathlike object or string representing a file

Transformation filenames.

out_lrmask_postfix : a unicode string

Suffix to be added to the Low resolution input_masks. (Nipype default value: _LRmask)

out_srmask_postfix : a unicode string

Suffix to be added to the SR reconstruction filename to construct output SR mask filename. (Nipype default value: _srMask)

output_lrmasks : a list of items which are a pathlike object or string representing a file

Output low-resolution reconstruction refined masks.

output_srmask : a pathlike object or string representing a file

Output super-resolution reconstruction refined mask.

pymialsrtk.interfaces.postprocess.binarize_image(input_image)