RF: Remove alternate precomputed mask workflow

Author: mgxd

nibabies/workflows/anatomical/base.py

@@ -82,10 +82,7 @@ def init_infant_anat_wf(
     from niworkflows.engine.workflows import LiterateWorkflow as Workflow
 
     from ...utils.misc import fix_multi_source_name
-    from .brain_extraction import (
-        init_infant_brain_extraction_wf,
-        init_precomputed_mask_wf,
-    )
+    from .brain_extraction import init_infant_brain_extraction_wf
     from .norm import init_anat_norm_wf
     from .outputs import (
         init_anat_derivatives_wf,

nibabies/workflows/anatomical/brain_extraction.py

@@ -249,57 +249,6 @@ def init_infant_brain_extraction_wf(
     return workflow
 
 
-def init_precomputed_mask_wf(
-    bspline_fitting_distance=200, omp_nthreads=None, name="precomputed_mask_wf"
-):
-    from nipype.interfaces.ants import N4BiasFieldCorrection
-    from niworkflows.interfaces.header import CopyXForm, ValidateImage
-    from niworkflows.interfaces.nibabel import ApplyMask, IntensityClip
-
-    workflow = pe.Workflow(name=name)
-    inputnode = pe.Node(niu.IdentityInterface(fields=["t1w", "t1w_mask"]), name="inputnode")
-    outputnode = pe.Node(
-        niu.IdentityInterface(fields=["t1w_preproc", "t1w_mask", "t1w_brain"]),
-        name="outputnode",
-    )
-
-    validate_mask = pe.Node(ValidateImage(), name="validate_mask")
-    fix_hdr = pe.Node(CopyXForm(), mem_gb=0.1, name="fix_hdr")
-    final_n4 = pe.Node(
-        N4BiasFieldCorrection(
-            dimension=3,
-            bspline_fitting_distance=bspline_fitting_distance,
-            save_bias=True,
-            copy_header=True,
-            n_iterations=[50] * 5,
-            convergence_threshold=1e-7,
-            rescale_intensities=True,
-            shrink_factor=4,
-        ),
-        n_procs=omp_nthreads,
-        name="final_n4",
-    )
-    final_clip = pe.Node(IntensityClip(p_min=5.0, p_max=99.5), name="final_clip")
-    apply_mask = pe.Node(ApplyMask(), name="apply_mask")
-
-    # fmt:off
-    workflow.connect([
-        (inputnode, validate_mask, [("t1w_mask", "in_file")]),
-        (validate_mask, fix_hdr, [("out_file", "in_file")]),
-        (inputnode, fix_hdr, [("t1w", "hdr_file")]),
-        (inputnode, final_n4, [("t1w", "input_image")]),
-        (fix_hdr, final_n4, [("out_file", "weight_image")]),
-        (fix_hdr, apply_mask, [("out_file", "in_mask")]),
-        (final_n4, apply_mask, [("output_image", "in_file")]),
-        (final_n4, final_clip, [("output_image", "in_file")]),
-        (fix_hdr, outputnode, [("out_file", "t1w_mask")]),
-        (final_clip, outputnode, [("out_file", "t1w_preproc")]),
-        (apply_mask, outputnode, [("out_file", "t1w_brain")]),
-    ])
-    # fmt:on
-    return workflow
-
-
 def _pop(in_files):
     if isinstance(in_files, (list, tuple)):
         return in_files[0]