rf: Reconstruct motion confounds from minimal derivatives

Author: effigies

fmriprep/workflows/bold/base.py

@@ -673,7 +673,8 @@ def init_bold_wf(
         ]),
         (bold_fit_wf, bold_confounds_wf, [
             ('outputnode.bold_mask', 'inputnode.bold_mask'),
-            ('outputnode.movpar_file', 'inputnode.movpar_file'),
+            ('outputnode.hmc_boldref', 'inputnode.hmc_boldref'),
+            ('outputnode.motion_xfm', 'inputnode.motion_xfm'),
             ('outputnode.rmsd_file', 'inputnode.rmsd_file'),
             ('outputnode.boldref2anat_xfm', 'inputnode.boldref2anat_xfm'),
             ('outputnode.dummy_scans', 'inputnode.skip_vols'),

fmriprep/workflows/bold/confounds.py

@@ -38,6 +38,8 @@
 from ...interfaces.confounds import (
     FilterDropped,
     FMRISummary,
+    FramewiseDisplacement,
+    FSLMotionParams,
     GatherConfounds,
     RenameACompCor,
 )
@@ -120,8 +122,8 @@ def init_bold_confs_wf(
         when available.
     bold_mask
         BOLD series mask
-    movpar_file
-        SPM-formatted motion parameters file
+    motion_xfm
+        ITK-formatted head motion transforms
     rmsd_file
         Root mean squared deviation as measured by ``fsl_motion_outliers`` [Jenkinson2002]_.
     skip_vols
@@ -221,7 +223,8 @@ def init_bold_confs_wf(
             fields=[
                 'bold',
                 'bold_mask',
-                'movpar_file',
+                'hmc_boldref',
+                'motion_xfm',
                 'rmsd_file',
                 'skip_vols',
                 't1w_mask',
@@ -262,8 +265,11 @@ def init_bold_confs_wf(
         mem_gb=mem_gb,
     )
 
+    # Motion parameters
+    motion_params = pe.Node(FSLMotionParams(), name='motion_params')
+
     # Frame displacement
-    fdisp = pe.Node(nac.FramewiseDisplacement(parameter_source='SPM'), name='fdisp', mem_gb=mem_gb)
+    fdisp = pe.Node(FramewiseDisplacement(), name='fdisp', mem_gb=mem_gb)
 
     # Generate aCompCor probseg maps
     acc_masks = pe.Node(aCompCorMasks(is_aseg=freesurfer), name='acc_masks')
@@ -367,12 +373,6 @@ def init_bold_confs_wf(
         mem_gb=0.01,
         run_without_submitting=True,
     )
-    add_motion_headers = pe.Node(
-        AddTSVHeader(columns=['trans_x', 'trans_y', 'trans_z', 'rot_x', 'rot_y', 'rot_z']),
-        name='add_motion_headers',
-        mem_gb=0.01,
-        run_without_submitting=True,
-    )
     add_rmsd_header = pe.Node(
         AddTSVHeader(columns=['rmsd']),
         name='add_rmsd_header',
@@ -518,12 +518,13 @@ def _select_cols(table):
             if not col.startswith(('a_comp_cor_', 't_comp_cor_', 'std_dvars'))
         ]
 
-    # fmt:off
     workflow.connect([
         # connect inputnode to each non-anatomical confound node
         (inputnode, dvars, [('bold', 'in_file'),
                             ('bold_mask', 'in_mask')]),
-        (inputnode, fdisp, [('movpar_file', 'in_file')]),
+        (inputnode, motion_params, [('motion_xfm', 'xfm_file'),
+                                    ('hmc_boldref', 'boldref_file')]),
+        (motion_params, fdisp, [('out_file', 'in_file')]),
         # Brain mask
         (inputnode, t1w_mask_tfm, [('t1w_mask', 'input_image'),
                                    ('bold_mask', 'reference_image'),
@@ -566,7 +567,6 @@ def _select_cols(table):
         (merge_rois, signals, [('out', 'label_files')]),
 
         # Collate computed confounds together
-        (inputnode, add_motion_headers, [('movpar_file', 'in_file')]),
         (inputnode, add_rmsd_header, [('rmsd_file', 'in_file')]),
         (dvars, add_dvars_header, [('out_nstd', 'in_file')]),
         (dvars, add_std_dvars_header, [('out_std', 'in_file')]),
@@ -576,7 +576,7 @@ def _select_cols(table):
                             ('pre_filter_file', 'cos_basis')]),
         (rename_acompcor, concat, [('components_file', 'acompcor')]),
         (crowncompcor, concat, [('components_file', 'crowncompcor')]),
-        (add_motion_headers, concat, [('out_file', 'motion')]),
+        (motion_params, concat, [('out_file', 'motion')]),
         (add_rmsd_header, concat, [('out_file', 'rmsd')]),
         (add_dvars_header, concat, [('out_file', 'dvars')]),
         (add_std_dvars_header, concat, [('out_file', 'std_dvars')]),
@@ -617,8 +617,7 @@ def _select_cols(table):
         (concat, conf_corr_plot, [('confounds_file', 'confounds_file'),
                                   (('confounds_file', _select_cols), 'columns')]),
         (conf_corr_plot, ds_report_conf_corr, [('out_file', 'in_file')]),
-    ])
-    # fmt: on
+    ])  # fmt: skip
 
     return workflow
 

fmriprep/workflows/bold/fit.py

@@ -178,8 +178,6 @@ def init_bold_fit_wf(
     boldref2fmap_xfm
         Affine transform mapping from BOLD reference space to the fieldmap
         space, if applicable.
-    movpar_file
-        MCFLIRT motion parameters, normalized to SPM format (X, Y, Z, Rx, Ry, Rz)
     rmsd_file
         Root mean squared deviation as measured by ``fsl_motion_outliers`` [Jenkinson2002]_.
     dummy_scans
@@ -287,7 +285,6 @@ def init_bold_fit_wf(
                 'motion_xfm',
                 'boldref2anat_xfm',
                 'boldref2fmap_xfm',
-                'movpar_file',
                 'rmsd_file',
             ],
         ),
@@ -303,7 +300,7 @@ def init_bold_fit_wf(
     )
     fmapref_buffer = pe.Node(niu.Function(function=_select_ref), name='fmapref_buffer')
     hmc_buffer = pe.Node(
-        niu.IdentityInterface(fields=['hmc_xforms', 'movpar_file', 'rmsd_file']), name='hmc_buffer'
+        niu.IdentityInterface(fields=['hmc_xforms', 'rmsd_file']), name='hmc_buffer'
     )
     fmapreg_buffer = pe.Node(
         niu.IdentityInterface(fields=['boldref2fmap_xfm']), name='fmapreg_buffer'
@@ -357,7 +354,6 @@ def init_bold_fit_wf(
         (fmapreg_buffer, outputnode, [('boldref2fmap_xfm', 'boldref2fmap_xfm')]),
         (hmc_buffer, outputnode, [
             ('hmc_xforms', 'motion_xfm'),
-            ('movpar_file', 'movpar_file'),
             ('rmsd_file', 'rmsd_file'),
         ]),
         (inputnode, func_fit_reports_wf, [
@@ -449,7 +445,6 @@ def init_bold_fit_wf(
             ]),
             (bold_hmc_wf, ds_hmc_wf, [('outputnode.xforms', 'inputnode.xforms')]),
             (bold_hmc_wf, hmc_buffer, [
-                ('outputnode.movpar_file', 'movpar_file'),
                 ('outputnode.rmsd_file', 'rmsd_file'),
             ]),
             (ds_hmc_wf, hmc_buffer, [('outputnode.xforms', 'hmc_xforms')]),

fmriprep/workflows/bold/hmc.py

@@ -32,8 +32,6 @@
 from nipype.interfaces import utility as niu
 from nipype.pipeline import engine as pe
 
-from ...config import DEFAULT_MEMORY_MIN_GB
-
 
 def init_bold_hmc_wf(mem_gb: float, omp_nthreads: int, name: str = 'bold_hmc_wf'):
     """
@@ -73,14 +71,11 @@ def init_bold_hmc_wf(mem_gb: float, omp_nthreads: int, name: str = 'bold_hmc_wf'
     -------
     xforms
         ITKTransform file aligning each volume to ``ref_image``
-    movpar_file
-        MCFLIRT motion parameters, normalized to SPM format (X, Y, Z, Rx, Ry, Rz)
     rmsd_file
         Root mean squared deviation as measured by ``fsl_motion_outliers`` [Jenkinson2002]_.
 
     """
     from niworkflows.engine.workflows import LiterateWorkflow as Workflow
-    from niworkflows.interfaces.confounds import NormalizeMotionParams
     from niworkflows.interfaces.itk import MCFLIRT2ITK
 
     workflow = Workflow(name=name)
@@ -94,9 +89,7 @@ def init_bold_hmc_wf(mem_gb: float, omp_nthreads: int, name: str = 'bold_hmc_wf'
     inputnode = pe.Node(
         niu.IdentityInterface(fields=['bold_file', 'raw_ref_image']), name='inputnode'
     )
-    outputnode = pe.Node(
-        niu.IdentityInterface(fields=['xforms', 'movpar_file', 'rmsd_file']), name='outputnode'
-    )
+    outputnode = pe.Node(niu.IdentityInterface(fields=['xforms', 'rmsd_file']), name='outputnode')
 
     # Head motion correction (hmc)
     mcflirt = pe.Node(
@@ -107,25 +100,17 @@ def init_bold_hmc_wf(mem_gb: float, omp_nthreads: int, name: str = 'bold_hmc_wf'
 
     fsl2itk = pe.Node(MCFLIRT2ITK(), name='fsl2itk', mem_gb=0.05, n_procs=omp_nthreads)
 
-    normalize_motion = pe.Node(
-        NormalizeMotionParams(format='FSL'), name='normalize_motion', mem_gb=DEFAULT_MEMORY_MIN_GB
-    )
-
     def _pick_rel(rms_files):
         return rms_files[-1]
 
-    # fmt:off
     workflow.connect([
         (inputnode, mcflirt, [('raw_ref_image', 'ref_file'),
                               ('bold_file', 'in_file')]),
         (inputnode, fsl2itk, [('raw_ref_image', 'in_source'),
                               ('raw_ref_image', 'in_reference')]),
         (mcflirt, fsl2itk, [('mat_file', 'in_files')]),
-        (mcflirt, normalize_motion, [('par_file', 'in_file')]),
         (mcflirt, outputnode, [(('rms_files', _pick_rel), 'rmsd_file')]),
         (fsl2itk, outputnode, [('out_file', 'xforms')]),
-        (normalize_motion, outputnode, [('out_file', 'movpar_file')]),
-    ])
-    # fmt:on
+    ])  # fmt:skip
 
     return workflow