dmriprep.workflows package

Submodules

dmriprep.workflows.anatomical module

Orchestrating the T1w preprocessing workflows

dmriprep.workflows.anatomical.init_anat_preproc_wf()[source]
dmriprep.workflows.anatomical.init_anat_preproc_wf()[source]

dmriprep.workflows.base module

dMRIprep base processing workflows

dmriprep.workflows.base.init_dmriprep_wf(layout, output_dir, subject_list, session_list, concat_dwis, b0_thresh, output_resolution, bet_dwi, bet_mag, acqp_file, slspec_file, omp_nthreads, ignore, use_ants, use_brainsuite, work_dir, synb0_dir)[source]

This workflow organizes the execusion of dMRIprep, with a sub-workflow for each subject.

(Source code)

from collections import namedtuple from dmriprep.workflows.base import init_dmriprep_wf BIDSLayout = namedtuple(‘BIDSLayout’, [‘root’]) wf = init_dmriprep_wf(

layout=BIDSLayout(‘.’, validate=False), output_dir=’.’, subject_list=[‘dmripreptest’], session_list=[], concat_dwis=[], b0_thresh=5, output_resolution=(1, 1, 1), bet_dwi=0.3, bet_mag=0.3, acqp_file=’’, omp_nthreads=1, ignore=[], use_ants=False, use_brainsuite=False, work_dir=’.’, synb0_dir=’’

)

Parameters

layout: BIDSLayout object

BIDS dataset layout

output_dir: str

Directory in which to save derivatives

subject_list: list

List of subject labels

session_list: list

List of session labels

concat_dwis: list

List of dwi images to concatenate (specified with the ‘acq-‘) tag

b0_thresh: int

Threshold for identifying bval as a b0

output_resolution: tuple

Output resolution of dwi image in x, y and z axes

bet_dwi: float

Fractional intensity threshold for BET on dwi image

bet_mag: float

Fractional intensity threshold for BET on magnitude image

omp_nthreads: int

Maximum number of threads an individual process may use

acqp_file: str

Optionally supply eddy acquisition parameters file

ignore: list

Preprocessing steps to skip (may include ‘denoise’, ‘unring’, ‘fieldmaps’)

work_dir: str

Directory in which to store workflow execution state and temporary files

synb0_dir: str

Direction in which synb0 derivatives are saved

dmriprep.workflows.base.init_single_subject_wf(name, layout, output_dir, subject_id, session_list, concat_dwis, b0_thresh, output_resolution, bet_dwi, bet_mag, omp_nthreads, acqp_file, slspec_file, ignore, use_ants, use_brainsuite, work_dir, synb0_dir)[source]

This workflow organizes the preprocessing pipeline for a single subject. It collects and reports information about the subject, and prepares sub-workflows to perform diffusion preprocessing.

Diffusion preprocessing is performed using a separate workflow for each individual dwi series.

(Source code)

from collections import namedtuple from dmriprep.workflows.base import init_single_subject_wf BIDSLayout = namedtuple(‘BIDSLayout’, [‘root’]) wf = init_single_subject_wf(

name=’single_subject_wf’, layout=BIDSLayout, output_dir=’.’, subject_id=’test’, session_list=[], concat_dwis=[], b0_thresh=5, output_resolution=(1, 1, 1), bet_dwi=0.3, bet_mag=0.3, acqp_file=’’, omp_nthreads=1, ignore=[], use_ants=False, use_brainsuite=False, work_dir=’.’, synb0_dir=’’

)

Parameters

name: layout: BIDSLayout object

BIDS dataset layout

output_dir: str

Directory in which to save derivatives

subject_id: str

Single subject label

session_list: list

List of sessions

concat_dwis: list

List of dwi images to concatenate (specified with the ‘acq-‘) tag

b0_thresh: int

Threshold for identifying bval as a b0

output_resolution: tuple

Output resolution of dwi image in x, y and z axes

bet_dwi: float

Fractional intensity threshold for BET on dwi image

bet_mag: float

Fractional intensity threshold for BET on magnitude image

acqp_file: str

Optional acquisition parameters file

omp_nthreads: int

Maximum number of threads an individual process may use

ignore: list

Preprocessing steps to skip (may include ‘denoise’, ‘unring’, ‘fieldmaps’)

work_dir: str

Directory in which to store workflow execution state and temporary files

synb0_dir: str

Directory in which synb0 derivatives are saved

dmriprep.workflows.base.init_dmriprep_wf(layout, output_dir, subject_list, session_list, concat_dwis, b0_thresh, output_resolution, bet_dwi, bet_mag, acqp_file, slspec_file, omp_nthreads, ignore, use_ants, use_brainsuite, work_dir, synb0_dir)[source]

This workflow organizes the execusion of dMRIprep, with a sub-workflow for each subject.

(Source code)

from collections import namedtuple from dmriprep.workflows.base import init_dmriprep_wf BIDSLayout = namedtuple(‘BIDSLayout’, [‘root’]) wf = init_dmriprep_wf(

layout=BIDSLayout(‘.’, validate=False), output_dir=’.’, subject_list=[‘dmripreptest’], session_list=[], concat_dwis=[], b0_thresh=5, output_resolution=(1, 1, 1), bet_dwi=0.3, bet_mag=0.3, acqp_file=’’, omp_nthreads=1, ignore=[], use_ants=False, use_brainsuite=False, work_dir=’.’, synb0_dir=’’

)

Parameters

layout: BIDSLayout object

BIDS dataset layout

output_dir: str

Directory in which to save derivatives

subject_list: list

List of subject labels

session_list: list

List of session labels

concat_dwis: list

List of dwi images to concatenate (specified with the ‘acq-‘) tag

b0_thresh: int

Threshold for identifying bval as a b0

output_resolution: tuple

Output resolution of dwi image in x, y and z axes

bet_dwi: float

Fractional intensity threshold for BET on dwi image

bet_mag: float

Fractional intensity threshold for BET on magnitude image

omp_nthreads: int

Maximum number of threads an individual process may use

acqp_file: str

Optionally supply eddy acquisition parameters file

ignore: list

Preprocessing steps to skip (may include ‘denoise’, ‘unring’, ‘fieldmaps’)

work_dir: str

Directory in which to store workflow execution state and temporary files

synb0_dir: str

Direction in which synb0 derivatives are saved

dmriprep.workflows.base.init_single_subject_wf(name, layout, output_dir, subject_id, session_list, concat_dwis, b0_thresh, output_resolution, bet_dwi, bet_mag, omp_nthreads, acqp_file, slspec_file, ignore, use_ants, use_brainsuite, work_dir, synb0_dir)[source]

This workflow organizes the preprocessing pipeline for a single subject. It collects and reports information about the subject, and prepares sub-workflows to perform diffusion preprocessing.

Diffusion preprocessing is performed using a separate workflow for each individual dwi series.

(Source code)

from collections import namedtuple from dmriprep.workflows.base import init_single_subject_wf BIDSLayout = namedtuple(‘BIDSLayout’, [‘root’]) wf = init_single_subject_wf(

name=’single_subject_wf’, layout=BIDSLayout, output_dir=’.’, subject_id=’test’, session_list=[], concat_dwis=[], b0_thresh=5, output_resolution=(1, 1, 1), bet_dwi=0.3, bet_mag=0.3, acqp_file=’’, omp_nthreads=1, ignore=[], use_ants=False, use_brainsuite=False, work_dir=’.’, synb0_dir=’’

)

Parameters

name: layout: BIDSLayout object

BIDS dataset layout

output_dir: str

Directory in which to save derivatives

subject_id: str

Single subject label

session_list: list

List of sessions

concat_dwis: list

List of dwi images to concatenate (specified with the ‘acq-‘) tag

b0_thresh: int

Threshold for identifying bval as a b0

output_resolution: tuple

Output resolution of dwi image in x, y and z axes

bet_dwi: float

Fractional intensity threshold for BET on dwi image

bet_mag: float

Fractional intensity threshold for BET on magnitude image

acqp_file: str

Optional acquisition parameters file

omp_nthreads: int

Maximum number of threads an individual process may use

ignore: list

Preprocessing steps to skip (may include ‘denoise’, ‘unring’, ‘fieldmaps’)

work_dir: str

Directory in which to store workflow execution state and temporary files

synb0_dir: str

Directory in which synb0 derivatives are saved

Module contents