FIX: Missing connections, surfaces, syntax

nibabies/workflows/anatomical/__init__.py

@@ -1 +1 @@
-from .base import init_infant_anat_wf
+from .base import init_infant_anat_wf, init_infant_single_anat_wf

nibabies/workflows/anatomical/base.py

@@ -46,8 +46,8 @@
     "subject_id",
     "anat2std_xfm",
     "std2anat_xfm",
-    "t1w2fsnative_xfm",
-    "fsnative2t1w_xfm",
+    "anat2fsnative_xfm",
+    "fsnative2anat_xfm",
     "surfaces",
     "morphometrics",
     "anat_aseg",
@@ -68,7 +68,7 @@ def init_infant_anat_wf(
     ants_affine_init: bool,
     t1w: list,
     t2w: list,
-    anat_modality: str,
+    contrast: ty.Literal['T1w', 'T2w'],
     bids_root: str | Path,
     derivatives: Derivatives,
     freesurfer: bool,
@@ -252,7 +252,7 @@ def init_infant_anat_wf(
 
     # Segmentation - initial implementation should be simple: JLF
     anat_seg_wf = init_anat_segmentations_wf(
-        anat_modality=anat_modality.capitalize(),  # TODO: Revisit this option
+        anat_modality=contrast.capitalize(),  # TODO: Revisit this option
         template_dir=segmentation_atlases,
         sloppy=sloppy,
         omp_nthreads=omp_nthreads,
@@ -625,7 +625,10 @@ def init_infant_single_anat_wf(
         aseg = derivatives.t2w_aseg
 
     config.loggers.workflow.info(
-        f"Derivatives used (%s):\n\t<mask - %s>\n\t<aseg %s>\n\t", contrast, bool(mask), bool(aseg)
+        f"Derivatives used (%s):\n\t\t<Mask: %s>\n\t\t<Aseg: %s>\n",
+        contrast,
+        bool(mask),
+        bool(aseg),
     )
 
     inputnode = pe.Node(
@@ -635,8 +638,8 @@ def init_infant_single_anat_wf(
     outputnode = pe.Node(niu.IdentityInterface(fields=ANAT_OUT_FIELDS), name="outputnode")
 
     desc = _gen_anat_wf_desc(
-        t1w=anat_files if contrast == 'T1w' else None,
-        t2w=anat_files if contrast == 'T2w' else None,
+        t1w=t1w or None,
+        t2w=t2w or None,
         mask=bool(mask),
     )
     workflow.__desc__ = desc.format(
@@ -686,31 +689,33 @@ def init_infant_single_anat_wf(
     # T2-only segmentation
     anat_norm_wf = init_anat_norm_wf(
         sloppy=sloppy,
-        omp_ntheads=omp_nthreads,
+        omp_nthreads=omp_nthreads,
         templates=spaces.get_spaces(nonstandard=False, dim=(3,)),
     )
+    # Aggregate mask, applied mask
+    mask_buffer = pe.Node(
+        niu.IdentityInterface(fields=['anat_mask', 'anat_brain']),
+        name='mask_buffer',
+    )
 
     if mask:
         from niworkflows.interfaces.nibabel import ApplyMask
 
+        anat_template_wf.inputs.inputnode.anat_mask = mask
         mask_ref = derivatives.references[f'{contrast.lower()}_mask']
-        anat_preproc_wf.inputnode.inputs.mask_reference = mask_ref
+        anat_template_wf.inputs.inputnode.mask_reference = mask_ref
 
         apply_deriv_mask = pe.Node(ApplyMask(), name='apply_deriv_mask')
         # fmt:off
         workflow.connect([
-            (anat_preproc_wf, anat_norm_wf, [
-                ('outputnode.anat_mask', 'inputnode.moving_mask')]),
+            (anat_template_wf, mask_buffer, [
+                ('outputnode.anat_mask', 'anat_mask')]),
             (anat_preproc_wf, apply_deriv_mask, [
                 ('outputnode.anat_preproc', 'in_file')]),
             (anat_template_wf, apply_deriv_mask, [
                 ('outputnode.anat_mask', 'in_mask')]),
-            (apply_deriv_mask, anat_seg_wf, [
-                ("out_mask", "inputnode.anat_brain")]),
-            (anat_template_wf, anat_derivatives_wf, [
-                ('outputnode.anat_mask', 'inputnode.anat_mask')]),
-            (anat_template_wf, outputnode, [
-                ('outputnode.anat_mask', 'anat_mask')]),
+            (apply_deriv_mask, mask_buffer, [
+                ('out_file', 'anat_brain')]),
         ])
         # fmt:on
 
@@ -726,18 +731,28 @@ def init_infant_single_anat_wf(
         )
         # fmt:off
         workflow.connect([
-            (anat_preproc_wf, brain_extraction_wf, [('outputnode.anat_preproc', 'inputnode.t2w_preproc')]),
-            (brain_extraction_wf, anat_seg_wf, [('outputnode.t2w_brain', 'inputnode.anat_brain')]),
-            (brain_extraction_wf, anat_norm_wf, [('outputnode.out_mask', 'inputnode.moving_mask')]),
-            (brain_extraction_wf, anat_derivatives_wf, [('outputnode.out_mask', 'inputnode.anat_mask')]),
+            (anat_preproc_wf, brain_extraction_wf, [
+                ('outputnode.anat_preproc', 'inputnode.t2w_preproc')]),
+            (brain_extraction_wf, mask_buffer, [
+                ('outputnode.t2w_brain', 'anat_brain'),
+                ('outputnode.out_mask', 'anat_mask')]),
         ])
         # fmt:on
 
+    if aseg:
+        anat_template_wf.inputs.inputnode.anat_aseg = aseg
+        aseg_ref = derivatives.references[f'{contrast.lower()}_aseg']
+        anat_template_wf.inputs.inputnode.aseg_reference = aseg_ref
+
+        workflow.connect(
+            anat_template_wf, 'outputnode.anat_aseg', anat_seg_wf, 'inputnode.anat_aseg'
+        )
+
     # fmt:off
     workflow.connect([
-        (inputnode, anat_template_wf, [("anat_file", "inputnode.anat_files")]),
-        (inputnode, anat_reports_wf, [("anat_file", "inputnode.source_file")]),
-        (inputnode, anat_norm_wf, [(("anat_file", fix_multi_source_name), "inputnode.orig_t1w")]),
+        (inputnode, anat_template_wf, [(contrast.lower(), "inputnode.anat_files")]),
+        (inputnode, anat_reports_wf, [(contrast.lower(), "inputnode.source_file")]),
+        (inputnode, anat_norm_wf, [((contrast.lower(), fix_multi_source_name), "inputnode.orig_t1w")]),
 
         (anat_template_wf, outputnode, [
             ("outputnode.anat_realign_xfm", "anat_ref_xfms")]),
@@ -750,19 +765,26 @@ def init_infant_single_anat_wf(
             ("outputnode.out_report", "inputnode.anat_conform_report")]),
         (anat_preproc_wf, anat_norm_wf, [
             ('outputnode.anat_preproc', 'inputnode.moving_image')]),
+        (anat_preproc_wf, outputnode, [
+            ('outputnode.anat_preproc', 'anat_preproc')]),
         (anat_preproc_wf, anat_derivatives_wf, [
             ('outputnode.anat_preproc', f'inputnode.{contrast.lower()}_preproc')]),
+        (mask_buffer, anat_derivatives_wf, [
+            ('anat_mask', 'inputnode.anat_mask')]),
+        (mask_buffer, outputnode, [
+            ('anat_mask', 'anat_mask')]),
+        (mask_buffer, anat_seg_wf, [('anat_brain', 'inputnode.anat_brain')]),
         (anat_seg_wf, outputnode, [
             ("outputnode.anat_dseg", "anat_dseg"),
             ("outputnode.anat_tpms", "anat_tpms")]),
         (anat_seg_wf, anat_derivatives_wf, [
             ("outputnode.anat_dseg", "inputnode.anat_dseg"),
-            ("outputnode.anat_tpms", "inputnode.anat_tpms"),
-        ]),
+            ("outputnode.anat_tpms", "inputnode.anat_tpms")]),
+        (mask_buffer, anat_norm_wf, [
+            ('anat_mask', 'inputnode.moving_mask')]),
         (anat_seg_wf, anat_norm_wf, [
             ("outputnode.anat_dseg", "inputnode.moving_segmentation"),
             ("outputnode.anat_tpms", "inputnode.moving_tpms")]),
-
         (anat_norm_wf, anat_reports_wf, [("poutputnode.template", "inputnode.template")]),
         (anat_norm_wf, outputnode, [
             ("poutputnode.standardized", "std_preproc"),
@@ -777,7 +799,7 @@ def init_infant_single_anat_wf(
             ("outputnode.anat2std_xfm", "inputnode.anat2std_xfm"),
             ("outputnode.std2anat_xfm", "inputnode.std2anat_xfm")]),
         (outputnode, anat_reports_wf, [
-            ("anat_preproc", "inputnode.t1w_preproc"),
+            ("anat_preproc", "inputnode.anat_preproc"),
             ("anat_mask", "inputnode.anat_mask"),
             ("anat_dseg", "inputnode.anat_dseg"),
             ("std_preproc", "inputnode.std_t1w"),
@@ -828,17 +850,98 @@ def init_infant_single_anat_wf(
         else:
             # TODO: Use MCRIBS segmentation
             ...
-        if mask:
-            workflow.connect(
-                anat_template_wf, 'outputnode.anat_mask', surface_recon_wf, 'inputnode.anat_mask'
-            )
-        else:
-            workflow.connect(
-                brain_extraction_wf, 'outputnode.out_mask', surface_recon_wf, 'inputnode.anat_mask'
-            )
     else:
         raise NotImplementedError
 
+    # Anatomical ribbon file using HCP signed-distance volume method
+    anat_ribbon_wf = init_anat_ribbon_wf()
+
+    # fmt:off
+    workflow.connect([
+        (inputnode, surface_recon_wf, [
+            ("subject_id", "inputnode.subject_id"),
+            ("subjects_dir", "inputnode.subjects_dir")]),
+        (anat_template_wf, surface_recon_wf, [
+            ("outputnode.anat_ref", "inputnode.t1w"),
+        ]),
+        (mask_buffer, surface_recon_wf, [
+            ("anat_brain", "inputnode.skullstripped_t1"),
+            ("anat_mask", "inputnode.anat_mask")]),
+        (anat_preproc_wf, surface_recon_wf, [
+            ("outputnode.anat_preproc", "inputnode.corrected_t1")]),
+        (surface_recon_wf, outputnode, [
+            ("outputnode.subjects_dir", "subjects_dir"),
+            ("outputnode.subject_id", "subject_id"),
+            ("outputnode.t1w2fsnative_xfm", "anat2fsnative_xfm"),
+            ("outputnode.fsnative2t1w_xfm", "fsnative2anat_xfm"),
+            ("outputnode.surfaces", "surfaces"),
+            ("outputnode.morphometrics", "morphometrics"),
+            ("outputnode.out_aparc", "anat_aparc"),
+            ("outputnode.out_aseg", "anat_aseg"),
+        ]),
+        (mask_buffer, anat_ribbon_wf, [
+            ("anat_mask", "inputnode.t1w_mask"),
+        ]),
+        (surface_recon_wf, anat_ribbon_wf, [
+            ("outputnode.surfaces", "inputnode.surfaces"),
+        ]),
+        (anat_ribbon_wf, outputnode, [
+            ("outputnode.anat_ribbon", "anat_ribbon")
+        ]),
+        (anat_ribbon_wf, anat_derivatives_wf, [
+            ("outputnode.anat_ribbon", "inputnode.anat_ribbon"),
+        ]),
+        (surface_recon_wf, sphere_reg_wf, [
+            ('outputnode.subject_id', 'inputnode.subject_id'),
+            ('outputnode.subjects_dir', 'inputnode.subjects_dir'),
+        ]),
+        (surface_recon_wf, anat_reports_wf, [
+            ("outputnode.subject_id", "inputnode.subject_id"),
+            ("outputnode.subjects_dir", "inputnode.subjects_dir"),
+        ]),
+        (surface_recon_wf, anat_derivatives_wf, [
+            ("outputnode.out_aseg", "inputnode.anat_fs_aseg"),
+            ("outputnode.out_aparc", "inputnode.anat_fs_aparc"),
+            ("outputnode.t1w2fsnative_xfm", "inputnode.anat2fsnative_xfm"),
+            ("outputnode.fsnative2t1w_xfm", "inputnode.fsnative2anat_xfm"),
+            ("outputnode.surfaces", "inputnode.surfaces"),
+            ("outputnode.morphometrics", "inputnode.morphometrics"),
+        ]),
+        (sphere_reg_wf, outputnode, [
+            ('outputnode.sphere_reg', 'sphere_reg'),
+            ('outputnode.sphere_reg_fsLR', 'sphere_reg_fsLR')]),
+        (sphere_reg_wf, anat_derivatives_wf, [
+            ('outputnode.sphere_reg', 'inputnode.sphere_reg'),
+            ('outputnode.sphere_reg_fsLR', 'inputnode.sphere_reg_fsLR')]),
+    ])
+    # fmt: on
+
+    if cifti_output:
+        from nibabies.workflows.anatomical.resampling import (
+            init_anat_fsLR_resampling_wf,
+        )
+
+        is_mcribs = recon_method == "mcribs"
+        # handles morph_grayords_wf
+        anat_fsLR_resampling_wf = init_anat_fsLR_resampling_wf(cifti_output, mcribs=is_mcribs)
+        anat_derivatives_wf.get_node('inputnode').inputs.cifti_density = cifti_output
+        # fmt:off
+        workflow.connect([
+            (sphere_reg_wf, anat_fsLR_resampling_wf, [
+                ('outputnode.sphere_reg', 'inputnode.sphere_reg'),
+                ('outputnode.sphere_reg_fsLR', 'inputnode.sphere_reg_fsLR')]),
+            (surface_recon_wf, anat_fsLR_resampling_wf, [
+                ('outputnode.subject_id', 'inputnode.subject_id'),
+                ('outputnode.subjects_dir', 'inputnode.subjects_dir'),
+                ('outputnode.surfaces', 'inputnode.surfaces'),
+                ('outputnode.morphometrics', 'inputnode.morphometrics')]),
+            (anat_fsLR_resampling_wf, anat_derivatives_wf, [
+                ("outputnode.cifti_morph", "inputnode.cifti_morph"),
+                ("outputnode.cifti_metadata", "inputnode.cifti_metadata")]),
+            (anat_fsLR_resampling_wf, outputnode, [
+                ("outputnode.midthickness_fsLR", "midthickness_fsLR")])
+        ])
+        # fmt:on
     return workflow
 
 

nibabies/workflows/base.py

@@ -229,7 +229,8 @@ def init_single_subject_wf(
 
     anat_only = config.workflow.anat_only
     derivatives = Derivatives(bids_root=config.execution.layout.root)
-    anat_modality = "t1w" if subject_data["t1w"] else "t2w"
+    contrast = "T1w" if subject_data["t1w"] else "T2w"
+    single_modality = not (subject_data['t1w'] and subject_data['t2w'])
     # Make sure we always go through these two checks
     if not anat_only and not subject_data["bold"]:
         task_id = config.execution.task_id
@@ -347,7 +348,7 @@ def init_single_subject_wf(
     wf_args = dict(
         ants_affine_init=True,
         age_months=age,
-        anat_modality=anat_modality,
+        contrast=contrast,
         t1w=subject_data["t1w"],
         t2w=subject_data["t2w"],
         bids_root=config.execution.bids_dir,
@@ -364,33 +365,10 @@ def init_single_subject_wf(
         spaces=spaces,
         cifti_output=config.workflow.cifti_output,
     )
-
-    if subject_data['t1w'] and subject_data['t2w']:
-        anat_preproc_wf = init_infant_anat_wf(**wf_args)
-    else:
-        anat_preproc_wf = init_infant_single_anat_wf(
-            contrast='T1w' if subject_data['t1w'] else 'T2w', **wf_args
-        )
-    # Preprocessing of anatomical (includes registration to UNCInfant)
-    anat_preproc_wf = init_infant_anat_wf(
-        ants_affine_init=True,
-        age_months=age,
-        anat_modality=anat_modality,
-        t1w=subject_data["t1w"],
-        t2w=subject_data["t2w"],
-        bids_root=config.execution.bids_dir,
-        derivatives=derivatives,
-        freesurfer=config.workflow.run_reconall,
-        hires=config.workflow.hires,
-        longitudinal=config.workflow.longitudinal,
-        omp_nthreads=config.nipype.omp_nthreads,
-        output_dir=nibabies_dir,
-        segmentation_atlases=config.execution.segmentation_atlases_dir,
-        skull_strip_mode=config.workflow.skull_strip_t1w,
-        skull_strip_template=Reference.from_string(config.workflow.skull_strip_template)[0],
-        sloppy=config.execution.sloppy,
-        spaces=spaces,
-        cifti_output=config.workflow.cifti_output,
+    anat_preproc_wf = (
+        init_infant_anat_wf(**wf_args)
+        if not single_modality
+        else init_infant_single_anat_wf(**wf_args)
     )
 
     # fmt: off
@@ -424,17 +402,17 @@ def init_single_subject_wf(
 
     workflow.connect([
         (bidssrc, bids_info, [
-            (('t1w', fix_multi_source_name), 'in_file'),
+            ((contrast.lower(), fix_multi_source_name), 'in_file'),
         ]),
         (bidssrc, summary, [
             ('t1w', 't1w'),
             ('t2w', 't2w'),
         ]),
         (bidssrc, ds_report_summary, [
-            (('t1w', fix_multi_source_name), 'source_file'),
+            ((contrast.lower(), fix_multi_source_name), 'source_file'),
         ]),
         (bidssrc, ds_report_about, [
-            (('t1w', fix_multi_source_name), 'source_file'),
+            ((contrast.lower(), fix_multi_source_name), 'source_file'),
         ]),
     ])
     # fmt: on