dmriprep.workflows.dwi.resampling module

DWI resampling workflows (transform stage).

These workflows compose all estimated transforms and apply them in a single interpolation step, minimizing blurring and preserving signal quality.

class dmriprep.workflows.dwi.resampling.ResampleDWISeries(from_file=None, resource_monitor=None, **inputs)View on GitHub

Bases: SimpleInterface

Resample a 4D DWI series with composed transforms.

This interface composes all provided transforms (motion, coregistration, SDC) and applies them in a single interpolation step to each volume of the DWI series. This minimizes blurring compared to sequential resampling operations.

Mandatory Inputs:

  • dwi_file (a pathlike object or string representing an existing file) – DWI NIfTI file.

  • reference (a pathlike object or string representing an existing file) – Reference image defining output space.

Optional Inputs:

  • apply_sdc (a boolean) – Apply SDC. (Nipype default value: False)

  • coreg_xfm (a pathlike object or string representing an existing file) – Coregistration transform.

  • fmap_coeff (a pathlike object or string representing an existing file) – Fieldmap B-spline coefficients.

  • jacobian (a boolean) – Apply Jacobian modulation. (Nipype default value: False)

  • metadata (a dictionary with keys which are any value and with values which are any value) – DWI metadata.

  • motion_xfm (a list of items which are a pathlike object or string representing an existing file) – Per-volume motion transforms.

  • n_procs (an integer) – Number of parallel processes. (Nipype default value: 1)

  • order (an integer) – Interpolation order. (Nipype default value: 3)

Outputs:

out_file (a pathlike object or string representing an existing file) – Resampled DWI file.

dmriprep.workflows.dwi.resampling.init_dwi_native_wf(*, fieldmap_id=None, jacobian=False, omp_nthreads=1, name='dwi_native_wf')View on GitHub

Build a workflow to resample DWI to native (corrected) space.

This workflow composes all transforms (HMC + eddy + SDC) and applies them in a single interpolation step to the DWI data. The output remains in DWI native space but is corrected for all distortions.

Workflow Graph
../_images/dmriprep-workflows-dwi-resampling-1.png

(Source code, png, svg, pdf)

Parameters:

  • fieldmap_id – ID of the fieldmap used for SDC, if any.

  • jacobian – Whether to apply Jacobian modulation for SDC.

  • omp_nthreads – Number of threads for parallel processing.

  • name – Workflow name.

Inputs:

  • dwi_file – Original DWI NIfTI file.

  • dwi_mask – Brain mask in DWI space.

  • hmc_dwiref – HMC reference image.

  • motion_xfm – Per-volume motion transforms.

  • fmap_coeff – Fieldmap B-spline coefficients (if SDC).

  • metadata – DWI metadata dictionary.

Outputs:

  • dwi_preproc – Preprocessed DWI in native space.

  • dwi_ref – Reference image (first b=0 after correction).

dmriprep.workflows.dwi.resampling.init_dwi_std_wf(*, fieldmap_id=None, jacobian=False, omp_nthreads=1, name='dwi_std_wf')View on GitHub

Build a workflow to resample DWI to standard (anatomical) space.

This workflow composes all transforms (HMC + eddy + SDC + coregistration) and applies them in a single interpolation step. The output is in the anatomical (T1w) space.

Parameters:

  • fieldmap_id – ID of the fieldmap used for SDC, if any.

  • jacobian – Whether to apply Jacobian modulation for SDC.

  • omp_nthreads – Number of threads for parallel processing.

  • name – Workflow name.

Inputs:

  • dwi_file – Original DWI NIfTI file.

  • t1w_preproc – Preprocessed T1w image (defines output space).

  • t1w_mask – Brain mask in T1w space.

  • hmc_dwiref – HMC reference image.

  • motion_xfm – Per-volume motion transforms.

  • dwiref2anat_xfm – Transform from DWI reference to anatomical space.

  • fmap_coeff – Fieldmap B-spline coefficients (if SDC).

  • metadata – DWI metadata dictionary.

Outputs:

  • dwi_preproc – Preprocessed DWI in T1w space.

  • dwi_ref – Reference image in T1w space.

  • dwi_mask – Brain mask in T1w space.