qsiprep.workflows.dwi.fsl module

Implementing the FSL preprocessing workflow.

Implementing the FSL preprocessing workflow

qsiprep.workflows.dwi.fsl.init_fsl_hmc_wf(unit, source_file, t2w_sdc, slice_quality='outlier_n_sqr_stdev_map', name='fsl_hmc_wf')[source]

Build a workflow that runs the dwi preprocessing stages using FSL tools.

I couldn’t get this to work reliably unless everything was oriented in LAS+ before going to TOPUP and eddy. For this reason, if TOPUP is going to be used (for an epi fieldmap or an RPE series) or there is no fieldmap correction, operations occurring before eddy are done in LAS+. The fieldcoefs are applied during eddy’s run and the corrected series comes out. This is finally converted to LPS+ and sent to the rest of the pipeline.

If a GRE fieldmap is available, the correction is applied to eddy’s outputs after they have been converted back to LPS+.

Finally, if SyN is chosen, it is applied to the LPS+ converted, eddy-resampled data.

Parameters:

  • unit (PreprocUnit) – the DWI series to correct together and the fieldmap that corrects them

  • source_file (str) – Path to the source DWI file (used for report and derivative naming).

  • t2w_sdc (bool) – Whether a T2w image is available for distortion correction (used for DRBUDDI’s multi-modal registration).

  • slice_quality (str, optional) – Name of the eddy output that is sent to outputnode.slice_quality and outputnode.hmc_optimization_data. Default is 'outlier_n_sqr_stdev_map'.

  • name (str, optional) – Name of workflow (default: fsl_hmc_wf)

Inputs:

  • dwi_file (str) – DWI series. Possibly concatenated, denoised, etc

  • bvec_file (str) – bvec file

  • bval_file (str) – bval file

  • json_file (str) – path to sidecar json file for dwi_file

  • b0_indices (list) – Indexes into dwi_files that correspond to b=0 volumes

  • b0_images (list) – List of single b=0 volumes

  • original_files (list) – List of the files from which each DWI volume came. One per original file

  • t1_brain (str) – Skull stripped T1w image

  • t1_mask (str) – mask for t1_brain

qsiprep.workflows.dwi.fsl.init_fsl_hmc_wf(unit, source_file, t2w_sdc, slice_quality='outlier_n_sqr_stdev_map', name='fsl_hmc_wf')[source]

Build a workflow that runs the dwi preprocessing stages using FSL tools.

I couldn’t get this to work reliably unless everything was oriented in LAS+ before going to TOPUP and eddy. For this reason, if TOPUP is going to be used (for an epi fieldmap or an RPE series) or there is no fieldmap correction, operations occurring before eddy are done in LAS+. The fieldcoefs are applied during eddy’s run and the corrected series comes out. This is finally converted to LPS+ and sent to the rest of the pipeline.

If a GRE fieldmap is available, the correction is applied to eddy’s outputs after they have been converted back to LPS+.

Finally, if SyN is chosen, it is applied to the LPS+ converted, eddy-resampled data.

Parameters:

  • unit (PreprocUnit) – the DWI series to correct together and the fieldmap that corrects them

  • source_file (str) – Path to the source DWI file (used for report and derivative naming).

  • t2w_sdc (bool) – Whether a T2w image is available for distortion correction (used for DRBUDDI’s multi-modal registration).

  • slice_quality (str, optional) – Name of the eddy output that is sent to outputnode.slice_quality and outputnode.hmc_optimization_data. Default is 'outlier_n_sqr_stdev_map'.

  • name (str, optional) – Name of workflow (default: fsl_hmc_wf)

Inputs:

  • dwi_file (str) – DWI series. Possibly concatenated, denoised, etc

  • bvec_file (str) – bvec file

  • bval_file (str) – bval file

  • json_file (str) – path to sidecar json file for dwi_file

  • b0_indices (list) – Indexes into dwi_files that correspond to b=0 volumes

  • b0_images (list) – List of single b=0 volumes

  • original_files (list) – List of the files from which each DWI volume came. One per original file

  • t1_brain (str) – Skull stripped T1w image

  • t1_mask (str) – mask for t1_brain