Preprocess module¶

PyMIALSRTK preprocessing functions.

It includes BTK Non-local-mean denoising, slice intensity correction slice N4 bias field correction, slice-by-slice correct bias field, intensity standardization, histogram normalization and both manual or deep learning based automatic brain extraction.

class pymialsrtk.interfaces.preprocess.BrainExtraction(*args, **kwargs)[source]¶

Runs the automatic brain extraction module.

This module is based on a 2D U-Net (Ronneberger et al. [1]_) using the pre-trained weights from Salehi et al. [2]_.

References

[1]	Ronneberger et al.; Medical Image Computing and Computer Assisted Interventions, 2015. (link to paper)

[2]	Salehi et al.; arXiv, 2017. (link to paper)

Examples

>>> from pymialsrtk.interfaces.preprocess import BrainExtraction
>>> brainMask = BrainExtraction()
>>> brainmask.inputs.base_dir = '/my_directory'
>>> brainmask.inputs.in_file = 'sub-01_acq-haste_run-1_2w.nii.gz'
>>> brainmask.inputs.in_ckpt_loc = 'my_loc_checkpoint'
>>> brainmask.inputs.threshold_loc = 0.49
>>> brainmask.inputs.in_ckpt_seg = 'my_seg_checkpoint'
>>> brainmask.inputs.threshold_seg = 0.5
>>> brainmask.inputs.out_postfix = '_brainMask.nii.gz'
>>> brainmask.run() # doctest: +SKIP

input_spec¶: alias of BrainExtractionInputSpec

output_spec¶: alias of BrainExtractionOutputSpec

class pymialsrtk.interfaces.preprocess.BrainExtractionInputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the BrainExtraction interface.

base_dir <string>: BIDS root directory (required)

in_file <string>: Input image file (required)

in_ckpt_loc <string>: Network_checkpoint for localization (required)

threshold_loc <Float>: Threshold determining cutoff probability (default is 0.49)

in_ckpt_seg <string>: Network_checkpoint for segmentation

threshold_seg <Float>: Threshold determining cutoff probability (default is 0.5)

out_postfix <string>: Suffix of the automatically generated mask (default is ‘_brainMask.nii.gz’)

class pymialsrtk.interfaces.preprocess.BrainExtractionOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the BrainExtraction interface.

out_file <string>: Brain mask output image

class pymialsrtk.interfaces.preprocess.BtkNLMDenoising(*args, **kwargs)[source]¶

Runs the non-local mean denoising module.

It calls the Baby toolkit implementation by Rousseau et al. [1]_ of the method proposed by Coupé et al. [2]_.

References

[1]	Rousseau et al.; Computer Methods and Programs in Biomedicine, 2013. (link to paper)

[2]	Coupé et al.; IEEE Transactions on Medical Imaging, 2008. (link to paper)

Example

>>> from pymialsrtk.interfaces.preprocess import BtkNLMDenoising
>>> nlmDenoise = BtkNLMDenoising()
>>> nlmDenoise.inputs.bids_dir = '/my_directory'
>>> nlmDenoise.inputs.in_file = 'sub-01_acq-haste_run-1_T2w.nii.gz'
>>> nlmDenoise.inputs.in_mask = 'sub-01_acq-haste_run-1_mask.nii.gz'
>>> nlmDenoise.inputs.weight = 0.2
>>> nlmDenoise.run() # doctest: +SKIP

input_spec¶: alias of BtkNLMDenoisingInputSpec

output_spec¶: alias of BtkNLMDenoisingOutputSpec

class pymialsrtk.interfaces.preprocess.BtkNLMDenoisingInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the BtkNLMDenoising interface.

bids_dir <string>: BIDS root directory (required)

in_file <string>: Input image file (required)

in_mask <string>: Mask of the input image

out_postfix <string>: suffix added to input image filename to construct output filename (default is ‘_nlm’)

weight <float>: smoothing parameter (high beta produces smoother result, default is 0.1)

class pymialsrtk.interfaces.preprocess.BtkNLMDenoisingOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the BtkNLMDenoising interface.

out_file <string>: Output denoised image file

class pymialsrtk.interfaces.preprocess.FilteringByRunid(*args, **kwargs)[source]¶

Runs a filtering of files.

This module filters the input files matching the specified run-ids. Other files are discarded.

Examples

>>> from pymialsrtk.interfaces.preprocess import FilteringByRunid
>>> stacksFiltering = FilteringByRunid()
>>> stacksFiltering.inputs.input_masks = ['sub-01_run-1_mask.nii.gz', 'sub-01_run-4_mask.nii.gz', 'sub-01_run-2_mask.nii.gz']
>>> stacksFiltering.inputs.stacks_id = [1,2]
>>> stacksFiltering.run() # doctest: +SKIP

input_spec¶: alias of FilteringByRunidInputSpec

output_spec¶: alias of FilteringByRunidOutputSpec

class pymialsrtk.interfaces.preprocess.FilteringByRunidInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the FilteringByRunid interface.

input_files <list<string>>: Input brain masks on which motion is computed.

stacks_id <list<string>>: List of stacks id to be kept

class pymialsrtk.interfaces.preprocess.FilteringByRunidOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the FilteringByRunid interface.

output_files <list<string>>: Filtered files.

class pymialsrtk.interfaces.preprocess.MialsrtkCorrectSliceIntensity(*args, **kwargs)[source]¶

Runs the MIAL SRTK mean slice intensity correction module.

Example

>>> from pymialsrtk.interfaces.preprocess import MialsrtkCorrectSliceIntensity
>>> sliceIntensityCorr = MialsrtkCorrectSliceIntensity()
>>> sliceIntensityCorr.inputs.bids_dir = '/my_directory'
>>> sliceIntensityCorr.inputs.in_file = 'sub-01_acq-haste_run-1_T2w.nii.gz'
>>> sliceIntensityCorr.inputs.in_mask = 'sub-01_acq-haste_run-1_mask.nii.gz'
>>> sliceIntensityCorr.run() # doctest: +SKIP

input_spec¶: alias of MialsrtkCorrectSliceIntensityInputSpec

output_spec¶: alias of MialsrtkCorrectSliceIntensityOutputSpec

class pymialsrtk.interfaces.preprocess.MialsrtkCorrectSliceIntensityInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the MialsrtkCorrectSliceIntensity interface.

bids_dir <string>: BIDS root directory (required)

in_file <string>: Input image file (required)

in_mask <string>: Masks of the input image

out_postfix <string>: suffix added to image filename to construct output filename (default is ‘’)

class pymialsrtk.interfaces.preprocess.MialsrtkCorrectSliceIntensityOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MialsrtkCorrectSliceIntensity interface.

out_file <string>: Output corrected image file

class pymialsrtk.interfaces.preprocess.MialsrtkHistogramNormalization(*args, **kwargs)[source]¶

Runs the MIAL SRTK histogram normalizaton module.

This module implements the method proposed by Nyúl et al. [1]_.

References

[1]	Nyúl et al.; Medical Imaging, IEEE Transactions, 2000. (link to paper)

Example

>>> from pymialsrtk.interfaces.preprocess import MialsrtkHistogramNormalization
>>> histNorm = MialsrtkHistogramNormalization()
>>> histNorm.inputs.bids_dir = '/my_directory'
>>> histNorm.inputs.input_images = ['sub-01_acq-haste_run-1_T2w.nii.gz','sub-01_acq-haste_run-2_T2w.nii.gz']
>>> histNorm.inputs.input_masks = ['sub-01_acq-haste_run-1_mask.nii.gz','sub-01_acq-haste_run-2_mask.nii.gz']
>>> histNorm.run()  # doctest: +SKIP

input_spec¶: alias of MialsrtkHistogramNormalizationInputSpec

output_spec¶: alias of MialsrtkHistogramNormalizationOutputSpec

class pymialsrtk.interfaces.preprocess.MialsrtkHistogramNormalizationInputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MialsrtkHistogramNormalization interface.

bids_dir <string>: BIDS root directory (required)

input_images <list<string>>: Input image filenames (required)

input_masks <list<string>>: Masks of the input images

out_postfix <string>: suffix added to image filenames to construct output normalized image filenames (default is ‘_histnorm’)

class pymialsrtk.interfaces.preprocess.MialsrtkHistogramNormalizationOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MialsrtkHistogramNormalization interface.

output_images list<<string>>: Output histogram normalized images

class pymialsrtk.interfaces.preprocess.MialsrtkIntensityStandardization(*args, **kwargs)[source]¶

Runs the MIAL SRTK intensity standardization module.

This module rescales image intensity by linear transformation

Example

>>> from pymialsrtk.interfaces.preprocess import MialsrtkIntensityStandardization
>>> intensityStandardization= MialsrtkIntensityStandardization()
>>> intensityStandardization.inputs.bids_dir = '/my_directory'
>>> intensityStandardization.inputs.input_images = ['sub-01_acq-haste_run-1_T2w.nii.gz','sub-01_acq-haste_run-2_T2w.nii.gz']
>>> intensityStandardization.run() # doctest: +SKIP

input_spec¶: alias of MialsrtkIntensityStandardizationInputSpec

output_spec¶: alias of MialsrtkIntensityStandardizationOutputSpec

class pymialsrtk.interfaces.preprocess.MialsrtkIntensityStandardizationInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the MialsrtkIntensityStandardization interface.

bids_dir <string>: BIDS root directory (required)

input_images <list<string>>: Input image filenames (required)

in_max <float>: Maximum intensity (default is 255)

out_postfix <string>: suffix added to image filenames to construct output standardized image filenames (default is ‘’)

class pymialsrtk.interfaces.preprocess.MialsrtkIntensityStandardizationOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MialsrtkIntensityStandardization interface.

output_images list<<string>>: Output intensity standardized images

class pymialsrtk.interfaces.preprocess.MialsrtkMaskImage(*args, **kwargs)[source]¶

Runs the MIAL SRTK mask image module.

Example

>>> from pymialsrtk.interfaces.preprocess import MialsrtkMaskImage
>>> maskImg = MialsrtkMaskImage()
>>> maskImg.inputs.bids_dir = '/my_directory'
>>> maskImg.inputs.in_file = 'sub-01_acq-haste_run-1_T2w.nii.gz'
>>> maskImg.inputs.in_mask = 'sub-01_acq-haste_run-1_mask.nii.gz'
>>> maskImg.inputs.out_im_postfix = '_masked'
>>> maskImg.run() # doctest: +SKIP

input_spec¶: alias of MialsrtkMaskImageInputSpec

output_spec¶: alias of MialsrtkMaskImageOutputSpec

class pymialsrtk.interfaces.preprocess.MialsrtkMaskImageInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the MialsrtkMaskImage interface.

bids_dir <string>: BIDS root directory (required)

in_file <string>: Input image file (required)

in_mask <string>: Masks of the input image (required)

out_im_postfix <string>: suffix added to image filename to construct output masked image filename (default is ‘’)

class pymialsrtk.interfaces.preprocess.MialsrtkMaskImageOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MialsrtkMaskImage interface.

out_im_file <string>: Output masked image

class pymialsrtk.interfaces.preprocess.MialsrtkSliceBySliceCorrectBiasField(*args, **kwargs)[source]¶

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

Example

>>> from pymialsrtk.interfaces.preprocess import MialsrtkSliceBySliceCorrectBiasField
>>> biasFieldCorr = MialsrtkSliceBySliceCorrectBiasField()
>>> biasFieldCorr.inputs.bids_dir = '/my_directory'
>>> biasFieldCorr.inputs.in_file = 'sub-01_acq-haste_run-1_T2w.nii.gz'
>>> biasFieldCorr.inputs.in_mask = 'sub-01_acq-haste_run-1_mask.nii.gz'
>>> biasFieldCorr.inputs.in_field = 'sub-01_acq-haste_run-1_field.nii.gz'
>>> biasFieldCorr.run() # doctest: +SKIP

input_spec¶: alias of MialsrtkSliceBySliceCorrectBiasFieldInputSpec

output_spec¶: alias of MialsrtkSliceBySliceCorrectBiasFieldOutputSpec

class pymialsrtk.interfaces.preprocess.MialsrtkSliceBySliceCorrectBiasFieldInputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MialsrtkSliceBySliceCorrectBiasField interface.

bids_dir <string>: BIDS root directory (required)

in_file <string>: Input image file (required)

in_mask <string>: Masks of the input image (required)

in_field <string>: Bias field to correct in the input image (required)

out_im_postfix <string>: suffix added to image filename to construct output corrected image filename (default is ‘_bcorr’)

out_fld_postfix <string>: suffix added to image filename to construct output bias field image filename (default is ‘_n4bias’)

class pymialsrtk.interfaces.preprocess.MialsrtkSliceBySliceCorrectBiasFieldOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MialsrtkSliceBySliceCorrectBiasField interface.

out_im_file <string>: Output bias field corrected image file

class pymialsrtk.interfaces.preprocess.MialsrtkSliceBySliceN4BiasFieldCorrection(*args, **kwargs)[source]¶

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

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

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.in_file = 'sub-01_acq-haste_run-1_T2w.nii.gz'
>>> N4biasFieldCorr.inputs.in_mask = 'sub-01_acq-haste_run-1_mask.nii.gz'
>>> N4biasFieldCorr.run() # doctest: +SKIP

input_spec¶: alias of MialsrtkSliceBySliceN4BiasFieldCorrectionInputSpec

output_spec¶: alias of MialsrtkSliceBySliceN4BiasFieldCorrectionOutputSpec

class pymialsrtk.interfaces.preprocess.MialsrtkSliceBySliceN4BiasFieldCorrectionInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the MialsrtkSliceBySliceN4BiasFieldCorrection interface.

bids_dir <string>: BIDS root directory (required)

in_file <string>: Input image file (required)

in_mask <string>: Masks of the input image (required)

out_im_postfix <string>: suffix added to image filename to construct output corrected image filename (default is ‘_bcorr’)

out_fld_postfix <string>: suffix added to image filename to construct output bias field image filename (default is ‘_n4bias’)

class pymialsrtk.interfaces.preprocess.MialsrtkSliceBySliceN4BiasFieldCorrectionOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MialsrtkSliceBySliceN4BiasFieldCorrection interface.

out_im_file <string>: Output N4 bias field corrected image file

out_fld_file <string>: Output bias field

class pymialsrtk.interfaces.preprocess.MultipleBrainExtraction(*args, **kwargs)[source]¶

Runs on multiple images the automatic brain extraction module.

It calls on a list of images the pymialsrtk.interfaces.preprocess.BrainExtraction.BrainExtraction module that implements a brain extraction algorithm based on a 2D U-Net (Ronneberger et al. [1]_) using the pre-trained weights from Salehi et al. [2]_.

References

[1]	Ronneberger et al.; Medical Image Computing and Computer Assisted Interventions, 2015. (link to paper)

[2]	Salehi et al.; arXiv, 2017. (link to paper)

input_spec¶: alias of MultipleBrainExtractionInputSpec

output_spec¶: alias of MultipleBrainExtractionOutputSpec

class pymialsrtk.interfaces.preprocess.MultipleBrainExtractionInputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MultipleBrainExtraction interface.

bids_dir <string>: BIDS root directory (required)

input_images list<<string>>: List of input image file (required)

in_ckpt_loc <string>: Network_checkpoint for localization (required)

threshold_loc <Float>: Threshold determining cutoff probability (default is 0.49)

in_ckpt_seg <string>: Network_checkpoint for segmentation

threshold_seg <Float>: Threshold determining cutoff probability (default is 0.5)

out_postfix <string>: Suffix of the automatically generated mask (default is ‘_brainMask’)

class pymialsrtk.interfaces.preprocess.MultipleBrainExtractionOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MultipleBrainExtraction interface.

output_images list<<string>>: Output masks

class pymialsrtk.interfaces.preprocess.MultipleBtkNLMDenoising(*args, **kwargs)[source]¶

Apply the non-local mean (NLM) denoising module on multiple inputs.

It runs for each input image the interface pymialsrtk.interfaces.preprocess.BtkNLMDenoising to the NLM denoising implementation by Rousseau et al. [1]_ of the method proposed by Coupé et al. [2]_.

References

[1]	Rousseau et al.; Computer Methods and Programs in Biomedicine, 2013. (link to paper)

[2]	Coupé et al.; IEEE Transactions on Medical Imaging, 2008. (link to paper)

Example

>>> from pymialsrtk.interfaces.preprocess import MultipleBtkNLMDenoising
>>> multiNlmDenoise = MultipleBtkNLMDenoising()
>>> multiNlmDenoise.inputs.bids_dir = '/my_directory'
>>> multiNlmDenoise.inputs.in_file = ['sub-01_acq-haste_run-1_T2w.nii.gz', 'sub-01_acq-haste_run-1_2w.nii.gz']
>>> multiNlmDenoise.inputs.in_mask = ['sub-01_acq-haste_run-1_mask.nii.gz', 'sub-01_acq-haste_run-2_mask.nii.gz']
>>> multiNlmDenoise.run() # doctest: +SKIP

input_spec¶: alias of MultipleBtkNLMDenoisingInputSpec

output_spec¶: alias of MultipleBtkNLMDenoisingOutputSpec

class pymialsrtk.interfaces.preprocess.MultipleBtkNLMDenoisingInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the MultipleBtkNLMDenoising interface.

bids_dir <string>: BIDS root directory (required)

input_images <list<string>>: Input image files (required)

input_masks <list<string>>: Masks of the input images

out_postfix <string>: suffix added to images files to construct output filenames (default is ‘_nlm’)

weight <float>: smoothing parameter (high beta produces smoother result, default is 0.1)

class pymialsrtk.interfaces.preprocess.MultipleBtkNLMDenoisingOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MultipleBtkNLMDenoising interface.

output_images list<<string>>: Output denoised images

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkCorrectSliceIntensity(*args, **kwargs)[source]¶

Apply the MIAL SRTK slice intensity correction module on multiple images. Calls MialsrtkCorrectSliceIntensity interface with a list of images/masks.

Example

>>> from pymialsrtk.interfaces.preprocess import MultipleMialsrtkCorrectSliceIntensity
>>> multiSliceIntensityCorr = MialsrtkCorrectSliceIntensity()
>>> multiSliceIntensityCorr.inputs.bids_dir = '/my_directory'
>>> multiSliceIntensityCorr.inputs.in_file = ['sub-01_acq-haste_run-1_T2w.nii.gz', 'sub-01_acq-haste_run-2_T2w.nii.gz']
>>> multiSliceIntensityCorr.inputs.in_mask = ['sub-01_acq-haste_run-2_mask.nii.gz', 'sub-01_acq-haste_run-2_mask.nii.gz']
>>> multiSliceIntensityCorr.run() # doctest: +SKIP

input_spec¶: alias of MultipleMialsrtkCorrectSliceIntensityInputSpec

output_spec¶: alias of MultipleMialsrtkCorrectSliceIntensityOutputSpec

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkCorrectSliceIntensityInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the MultipleMialsrtkCorrectSliceIntensity interface.

bids_dir <string>: BIDS root directory (required)

input_images <list<string>>: Input image files (required)

input_masks <list<string>>: Masks of the input images

out_postfix <string>: suffix added to images files to construct output filenames (default is ‘’)

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkCorrectSliceIntensityOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MultipleMialsrtkCorrectSliceIntensity interface.

output_images list<<string>>: Output slice intensity corrected images

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkMaskImage(*args, **kwargs)[source]¶

Runs the MIAL SRTK mask image module on multiple images.

It calls the pymialsrtk.interfaces.preprocess.MialsrtkMaskImage interface with a list of images/masks.

Example

>>> from pymialsrtk.interfaces.preprocess import MultipleMialsrtkMaskImage
>>> multiMaskImg = MultipleMialsrtkMaskImage()
>>> multiMaskImg.inputs.bids_dir = '/my_directory'
>>> multiMaskImg.inputs.in_file = ['sub-01_acq-haste_run-1_T2w.nii.gz', 'sub-01_acq-haste_run-2_T2w.nii.gz']
>>> multiMaskImg.inputs.in_mask = ['sub-01_acq-haste_run-1_mask.nii.gz', 'sub-01_acq-haste_run-2_mask.nii.gz']
>>> multiMaskImg.inputs.out_im_postfix = '_masked'
>>> multiMaskImg.run() # doctest: +SKIP

input_spec¶: alias of MultipleMialsrtkMaskImageInputSpec

output_spec¶: alias of MultipleMialsrtkMaskImageOutputSpec

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkMaskImageInputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MultipleMialsrtkMaskImage interface.

bids_dir <string>: BIDS root directory (required)

input_images <list<string>>: Input image files (required)

input_masks <list<string>>: Masks of the input images (required)

input_fields <list<string>>: Bias fields to correct in the input images (required)

out_im_postfix <string>: suffix added to image filename to construct output masked image filenames (default is ‘’)

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkMaskImageOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MultipleMialsrtkMaskImage interface.

output_images list<<string>>: Output masked images

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkSliceBySliceCorrectBiasField(*args, **kwargs)[source]¶

Runs the MIAL SRTK slice by slice bias field correction module on multiple images.

It calls pymialsrtk.interfaces.preprocess.MialsrtkSliceBySliceCorrectBiasField interface with a list of images/masks/fields.

Example

>>> from pymialsrtk.interfaces.preprocess import MultipleMialsrtkSliceBySliceN4BiasFieldCorrection
>>> multiN4biasFieldCorr = MialsrtkSliceBySliceN4BiasFieldCorrection()
>>> multiN4biasFieldCorr.inputs.bids_dir = '/my_directory'
>>> multiN4biasFieldCorr.inputs.input_images = ['sub-01_acq-haste_run-1_T2w.nii.gz', 'sub-01_acq-haste_run-2_T2w.nii.gz']
>>> multiN4biasFieldCorr.inputs.input_masks = ['sub-01_acq-haste_run-1_mask.nii.gz', 'sub-01_acq-haste_run-2_mask.nii.gz']
>>> multiN4biasFieldCorr.inputs.input_fields = ['sub-01_acq-haste_run-1_field.nii.gz', 'sub-01_acq-haste_run-2_field.nii.gz']
>>> multiN4biasFieldCorr.run() # doctest: +SKIP

input_spec¶: alias of MultipleMialsrtkSliceBySliceCorrectBiasFieldInputSpec

output_spec¶: alias of MultipleMialsrtkSliceBySliceCorrectBiasFieldOutputSpec

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkSliceBySliceCorrectBiasFieldInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the MultipleMialsrtkSliceBySliceCorrectBiasField interface.

bids_dir <string>: BIDS root directory (required)

input_images <list<string>>: Input image files (required)

input_masks <list<string>>: Masks of the input images (required)

input_fields <list<string>>: Bias fields to correct in the input images (required)

out_im_postfix <string>: suffix added to image filename to construct output corrected image filename (default is ‘_bcorr’)

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkSliceBySliceCorrectBiasFieldOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MultipleMialsrtkSliceBySliceCorrectBiasField interface.

output_images list<<string>>: Output bias field corrected images

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkSliceBySliceN4BiasFieldCorrection(*args, **kwargs)[source]¶

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

Calls MialsrtkSliceBySliceN4BiasFieldCorrection interface that implements the method proposed by Tustison et al. [1]_ with a list of images/masks.

References

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

Example

>>> from pymialsrtk.interfaces.preprocess import MultipleMialsrtkSliceBySliceN4BiasFieldCorrection
>>> multiN4biasFieldCorr = MialsrtkSliceBySliceN4BiasFieldCorrection()
>>> multiN4biasFieldCorr.inputs.bids_dir = '/my_directory'
>>> multiN4biasFieldCorr.inputs.input_images = ['sub-01_acq-haste_run-1_T2w.nii.gz', 'sub-01_acq-haste_run-2_T2w.nii.gz']
>>> multiN4biasFieldCorr.inputs.inputs_masks = ['sub-01_acq-haste_run-1_mask.nii.gz', 'sub-01_acq-haste_run-2_mask.nii.gz']
>>> multiN4biasFieldCorr.run() # doctest: +SKIP

input_spec¶: alias of MultipleMialsrtkSliceBySliceN4BiasFieldCorrectionInputSpec

output_spec¶: alias of MultipleMialsrtkSliceBySliceN4BiasFieldCorrectionOutputSpec

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkSliceBySliceN4BiasFieldCorrectionInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the MultipleMialsrtkSliceBySliceN4BiasFieldCorrection interface.

bids_dir <string>: BIDS root directory (required)

input_images <list<string>>: Input image files (required)

input_masks <list<string>>: Masks of the input images (required)

out_im_postfix <string>: suffix added to image filename to construct output corrected image filename (default is ‘_bcorr’)

out_fld_postfix <string>: suffix added to image filename to construct output bias field image filename (default is ‘_n4bias’)

class pymialsrtk.interfaces.preprocess.MultipleMialsrtkSliceBySliceN4BiasFieldCorrectionOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the MultipleMialsrtkSliceBySliceN4BiasFieldCorrection interface.

output_images list<<string>>: Output N4 bias field corrected images (required)

output_fields list<<string>>: Output bias fields (required)

class pymialsrtk.interfaces.preprocess.StacksOrdering(*args, **kwargs)[source]¶

Runs the automatic ordering of stacks.

This module is based on the tracking of the brain mask centroid slice by slice.

Examples

>>> from pymialsrtk.interfaces.preprocess import StacksOrdering
>>> stacksOrdering = StacksOrdering()
>>> stacksOrdering.inputs.input_masks = ['sub-01_run-1_mask.nii.gz', 'sub-01_run-4_mask.nii.gz', 'sub-01_run-2_mask.nii.gz']
>>> stacksOrdering.run() # doctest: +SKIP

input_spec¶: alias of StacksOrderingInputSpec

output_spec¶: alias of StacksOrderingOutputSpec

class pymialsrtk.interfaces.preprocess.StacksOrderingInputSpec(*args, **kwargs)[source]¶

Class used to represent inputs of the StacksOrdering interface.

input_masks <list<string>>: Input brain masks on which motion is computed.

class pymialsrtk.interfaces.preprocess.StacksOrderingOutputSpec(*args, **kwargs)[source]¶

Class used to represent outputs of the StacksOrdering interface.

stacks_order <string>: Order of images’ run-id to be used for reconstruction