Source code for fmriprep.workflows.fieldmap.phdiff

#!/usr/bin/env python
# -*- coding: utf-8 -*-
# emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*-
# vi: set ft=python sts=4 ts=4 sw=4 et:
.. _sdc_phasediff :

Phase-difference B0 estimation

The field inhomogeneity inside the scanner (fieldmap) is proportional to the
phase drift between two subsequent :abbr:`GRE (gradient recall echo)`

Fieldmap preprocessing workflow for fieldmap data structure
8.9.1 in BIDS 1.0.0: one phase diff and at least one magnitude image


from niworkflows.nipype.interfaces import ants, fsl, utility as niu
from niworkflows.nipype.pipeline import engine as pe
# Note that demean_image imports from nipype
from niworkflows.nipype.workflows.dmri.fsl.utils import siemens2rads, demean_image, \
from niworkflows.interfaces.masks import BETRPT

from ...interfaces import (
    ReadSidecarJSON, IntraModalMerge, DerivativesDataSink,

[docs]def init_phdiff_wf(reportlets_dir, omp_nthreads, name='phdiff_wf'): """ Estimates the fieldmap using a phase-difference image and one or more magnitude images corresponding to two or more :abbr:`GRE (Gradient Echo sequence)` acquisitions. The `original code was taken from nipype <>`_. .. workflow :: :graph2use: orig :simple_form: yes from fmriprep.workflows.fieldmap.phdiff import init_phdiff_wf wf = init_phdiff_wf(reportlets_dir='.', omp_nthreads=1) Outputs:: outputnode.fmap_ref - The average magnitude image, skull-stripped outputnode.fmap_mask - The brain mask applied to the fieldmap outputnode.fmap - The estimated fieldmap in Hz """ inputnode = pe.Node(niu.IdentityInterface(fields=['magnitude', 'phasediff']), name='inputnode') outputnode = pe.Node(niu.IdentityInterface( fields=['fmap', 'fmap_ref', 'fmap_mask']), name='outputnode') def _pick1st(inlist): return inlist[0] # Read phasediff echo times meta = pe.Node(ReadSidecarJSON(), name='meta', mem_gb=0.01, run_without_submitting=True) # Merge input magnitude images magmrg = pe.Node(IntraModalMerge(), name='magmrg') # de-gradient the fields ("bias/illumination artifact") n4 = pe.Node(ants.N4BiasFieldCorrection(dimension=3, copy_header=True), name='n4', n_procs=omp_nthreads) bet = pe.Node(BETRPT(generate_report=True, frac=0.6, mask=True), name='bet') ds_fmap_mask = pe.Node(DerivativesDataSink( base_directory=reportlets_dir, suffix='fmap_mask'), name='ds_fmap_mask', mem_gb=0.01, run_without_submitting=True) # uses mask from bet; outputs a mask # dilate = pe.Node(fsl.maths.MathsCommand( # nan2zeros=True, args='-kernel sphere 5 -dilM'), name='MskDilate') # phase diff -> radians pha2rads = pe.Node(niu.Function(function=siemens2rads), name='pha2rads') # FSL PRELUDE will perform phase-unwrapping prelude = pe.Node(fsl.PRELUDE(), name='prelude') denoise = pe.Node(fsl.SpatialFilter(operation='median', kernel_shape='sphere', kernel_size=3), name='denoise') demean = pe.Node(niu.Function(function=demean_image), name='demean') cleanup_wf = cleanup_edge_pipeline(name="cleanup_wf") compfmap = pe.Node(Phasediff2Fieldmap(), name='compfmap') # The phdiff2fmap interface is equivalent to: # rad2rsec (using rads2radsec from nipype.workflows.dmri.fsl.utils) # pre_fugue = pe.Node(fsl.FUGUE(save_fmap=True), name='ComputeFieldmapFUGUE') # rsec2hz (divide by 2pi) workflow = pe.Workflow(name=name) workflow.connect([ (inputnode, meta, [('phasediff', 'in_file')]), (inputnode, magmrg, [('magnitude', 'in_files')]), (magmrg, n4, [('out_avg', 'input_image')]), (n4, prelude, [('output_image', 'magnitude_file')]), (n4, bet, [('output_image', 'in_file')]), (bet, prelude, [('mask_file', 'mask_file')]), (inputnode, pha2rads, [('phasediff', 'in_file')]), (pha2rads, prelude, [('out', 'phase_file')]), (meta, compfmap, [('out_dict', 'metadata')]), (prelude, denoise, [('unwrapped_phase_file', 'in_file')]), (denoise, demean, [('out_file', 'in_file')]), (demean, cleanup_wf, [('out', 'inputnode.in_file')]), (bet, cleanup_wf, [('mask_file', 'inputnode.in_mask')]), (cleanup_wf, compfmap, [('outputnode.out_file', 'in_file')]), (compfmap, outputnode, [('out_file', 'fmap')]), (bet, outputnode, [('mask_file', 'fmap_mask'), ('out_file', 'fmap_ref')]), (inputnode, ds_fmap_mask, [('phasediff', 'source_file')]), (bet, ds_fmap_mask, [('out_report', 'in_file')]), ]) return workflow