FIX: Clean up generated boilerplate (#200)

* FIX: Segmentation boilerplate

* FIX: Add infantFS boilerplate / bibliography entry

Author: mgxd

nibabies/data/boilerplate.bib

@@ -379,3 +379,16 @@ @article{uncinfant
 	title = {Infant Brain Atlases from Neonates to 1- and 2-Year-Olds},
 	journal = {{PLoS} {ONE}}
 }
+
+@article{infantfs,
+	doi = {10.1016/j.neuroimage.2020.116946},
+	url = {https://doi.org/10.1016%2Fj.neuroimage.2020.116946},
+	year = 2020,
+	month = {sep},
+	publisher = {Elsevier {BV}},
+	volume = {218},
+	pages = {116946},
+	author = {Lilla Zöllei and Juan Eugenio Iglesias and Yangming Ou and P. Ellen Grant and Bruce Fischl},
+	title = {Infant {FreeSurfer}: An automated segmentation and surface extraction pipeline for T1-weighted neuroimaging data of infants 0{\textendash}2 years},
+	journal = {{NeuroImage}}
+}

nibabies/workflows/anatomical/base.py

@@ -165,12 +165,6 @@ def init_infant_anat_wf(
 """
     )
 
-    desc += """\
-Brain tissue segmentation of cerebrospinal fluid (CSF),
-white-matter (WM) and gray-matter (GM) was performed on
-the brain-extracted T1w using ANTs JointFusion, distributed with ANTs {ants_ver}.
-"""
-
     wf.__desc__ = desc.format(
         ants_ver=ANTsInfo.version() or "(version unknown)",
         skullstrip_tpl=skull_strip_template.fullname,

nibabies/workflows/anatomical/segmentation.py

@@ -52,10 +52,19 @@ def init_anat_segmentations_wf(
         name="outputnode",
     )
 
+    wf.__desc__ = """Brain tissue segmentation of cerebrospinal fluid (CSF),
+white-matter (WM) and gray-matter (GM) was performed on """
+
     # Coerce segmentation labels to BIDS
     lut_anat_dseg = pe.Node(niu.Function(function=_apply_bids_lut), name="lut_anat_dseg")
 
     if not any((precomp_aseg, template_dir)):
+        from nipype.interfaces.fsl.base import Info as FSLInfo
+
+        wf.__desc__ += (
+            f"the brain-extracted T1w using FSL FAST {FSLInfo.version() or '(version unknown)'}."
+        )
+
         # Use FSL FAST for segmentations
         anat_dseg = pe.Node(
             fsl.FAST(segments=True, no_bias=True, probability_maps=True),
@@ -81,7 +90,13 @@ def init_anat_segmentations_wf(
         return wf
 
     # Joint Label Fusion
-    if template_dir:
+    elif template_dir:
+        from nipype.interfaces.ants.base import Info as ANTsInfo
+
+        wf.__desc__ += (
+            "the brain-extracted T1w using ANTs JointFusion, distributed with ANTs "
+            f"{ANTsInfo.version() or '(version unknown)'}."
+        )
         tmpl_anats, tmpl_segs = _parse_segmentation_atlases(anat_modality, template_dir)
 
         # register to templates
@@ -145,6 +160,7 @@ def init_anat_segmentations_wf(
         # fmt:on
 
     elif precomp_aseg:
+        wf.__desc__ += "a pre-computed segmentation."
         from niworkflows.interfaces.header import ValidateImage
 
         inputnode.inputs.anat_aseg = precomp_aseg

nibabies/workflows/anatomical/surfaces.py

@@ -11,7 +11,9 @@
 
 
 def init_infant_surface_recon_wf(*, age_months, use_aseg=False, name="infant_surface_recon_wf"):
-    wf = pe.Workflow(name=name)
+    from niworkflows.engine.workflows import LiterateWorkflow
+
+    wf = LiterateWorkflow(name=name)
     inputnode = pe.Node(
         niu.IdentityInterface(
             fields=[
@@ -41,6 +43,12 @@ def init_infant_surface_recon_wf(*, age_months, use_aseg=False, name="infant_sur
         name="outputnode",
     )
 
+    wf.__desc__ = f"""\
+Brain surfaces were reconstructed using `infant_recon_all` [FreeSurfer
+{fs.Info().looseversion() or "<ver>"}, RRID:SCR_001847, @infantfs],
+leveraging the masked, preprocessed T1w and anatomical segmentation.
+"""
+
     gen_recon_outdir = pe.Node(niu.Function(function=_gen_recon_dir), name="gen_recon_outdir")
 
     # inject the intensity-normalized skull-stripped t1w from the brain extraction workflow