nipype.interfaces.dipy.preprocess module

Denoise

Link to code

Bases: DipyBaseInterface

An interface to denoising diffusion datasets [Coupe2008]. See http://nipy.org/dipy/examples_built/denoise_nlmeans.html#example-denoise-nlmeans.

[Coupe2008]

Coupe P et al., An Optimized Blockwise Non Local Means Denoising Filter for 3D Magnetic Resonance Images, IEEE Transactions on Medical Imaging, 27(4):425-441, 2008.

Example

>>> import nipype.interfaces.dipy as dipy
>>> denoise = dipy.Denoise()
>>> denoise.inputs.in_file = 'diffusion.nii'
>>> denoise.run() # doctest: +SKIP

in_file : a pathlike object or string representing an existing file

The input 4D diffusion-weighted image file.

noise_model : ‘rician’ or ‘gaussian’

Noise distribution model. (Nipype default value: rician)

block_radius : an integer (int or long)

Block_radius. (Nipype default value: 5)

in_mask : a pathlike object or string representing an existing file

Brain mask.

noise_mask : a pathlike object or string representing an existing file

Mask in which the standard deviation of noise will be computed.

patch_radius : an integer (int or long)

Patch radius. (Nipype default value: 1)

signal_mask : a pathlike object or string representing an existing file

Mask in which the mean signal will be computed.

snr : a float

Manually set an SNR.

out_file : a pathlike object or string representing an existing file

Resample

Link to code

Bases: DipyBaseInterface

An interface to reslicing diffusion datasets. See http://nipy.org/dipy/examples_built/reslice_datasets.html#example-reslice-datasets.

Example

>>> import nipype.interfaces.dipy as dipy
>>> reslice = dipy.Resample()
>>> reslice.inputs.in_file = 'diffusion.nii'
>>> reslice.run() # doctest: +SKIP

in_file : a pathlike object or string representing an existing file

The input 4D diffusion-weighted image file.

interp : an integer (int or long)

Order of the interpolator (0 = nearest, 1 = linear, etc. (Nipype default value: 1)

vox_size : a tuple of the form: (a float, a float, a float)

Specify the new voxel zooms. If no vox_size is set, then isotropic regridding will be performed, with spacing equal to the smallest current zoom.

out_file : a pathlike object or string representing an existing file

nipype.interfaces.dipy.preprocess.nlmeans_proxy(in_file, settings, snr=None, smask=None, nmask=None, out_file=None)

Uses non-local means to denoise 4D datasets

nipype.interfaces.dipy.preprocess.resample_proxy(in_file, order=3, new_zooms=None, out_file=None)

Performs regridding of an image to set isotropic voxel sizes using dipy.