No subsample by default

README.md

@@ -33,9 +33,6 @@ We found that CIVET's implementation of the marching-cubes algorithm, `sphere_me
 than scikit-image's implementation, which requires FWHM blurring of the volume.
 Moreover, `sphere_mesh` guarantees a spherical topology.
 
-It is necessary to use the `-subsample` option for fetal brains to avoid
-"bridge" errors between tight (<1 voxel) sulcal walls.
-
 ## Surface Extraction Algorithm
 
 1. Proprocess mask using `mincmorph` to fill in disconnected voxels (improve mask quality)
@@ -71,6 +68,11 @@ individually and in parallel.
 
 ### Options
 
+#### `--subsample`
+
+It is necessary to use the `--subsample` option for fetal brains 29 GA
+and older to avoid "bridge" errors between narrow (<1 voxel) sulcal walls.
+
 #### `--mincmorph-iterations`
 
 Number of `mincmorph` iterations to perform on the mask before marching-cubes.

extract_cp/__main__.py

@@ -17,6 +17,8 @@
                     help='brain hemisphere side. "auto" => infer from file name')
 parser.add_argument('-p', '--pattern', default='**/*.mnc',
                     help='pattern for file names to include')
+parser.add_argument('--subsample', action='store_true',
+                    help='Use -subsample option for spehre_mesh, use with narrow sulci')
 parser.add_argument('--mincmorph-iterations', dest='mincmorph_iterations', type=int, default=5,
                     help='Number of mincmorph iterations. Mincmorph is a mask preprocessing step '
                          'which repairs disconnected voxels. A larger value may improve results '

extract_cp/extract_surface.py

@@ -19,7 +19,7 @@ def extract_surface(mask: Path, surface: Path, params: Parameters):
         with log_path.open('wb') as log:
             HemisphereMask(mask)\
                 .smoothen_using_mincmorph(iterations=params.mincmorph_iterations)\
-                .just_sphere_mesh(chosen_side, subsample=True)\
+                .just_sphere_mesh(chosen_side, subsample=params.subsample)\
                 .adapt_object_mesh(*params.adapt_object_mesh)\
                 .interpolate_with_sphere(chosen_side, *params.inflate_to_sphere_implicit)\
                 .save(surface, shell=__curry_log(log))

extract_cp/params.py

@@ -16,6 +16,7 @@ class Parameters:
     adapt_object_mesh: tuple[int, int, int]
     inflate_to_sphere_implicit: tuple[int, int]
     keep_mask: bool
+    subsample: bool
 
     def __post_init__(self):
         if not len(self.adapt_object_mesh) == 3:
@@ -30,14 +31,16 @@ def new(
             mincmorph_iterations: int,
             adapt_object_mesh: str,
             inflate_to_sphere_implicit: str,
-            keep_mask: bool
+            keep_mask: bool,
+            subsample: bool
     ) -> 'Parameters':
         return cls(
             side=side,
             mincmorph_iterations=mincmorph_iterations,
             adapt_object_mesh=_str2ints(adapt_object_mesh),
             inflate_to_sphere_implicit=_str2ints(inflate_to_sphere_implicit),
-            keep_mask=keep_mask
+            keep_mask=keep_mask,
+            subsample=subsample
         )
 
     @classmethod
@@ -47,7 +50,8 @@ def from_obj(cls, options) -> 'Parameters':
             mincmorph_iterations=options.mincmorph_iterations,
             adapt_object_mesh=options.adapt_object_mesh,
             inflate_to_sphere_implicit=options.inflate_to_sphere_implicit,
-            keep_mask=options.keep_mask
+            keep_mask=options.keep_mask,
+            subsample=options.subsample
         )
 
 

setup.py

@@ -2,15 +2,14 @@
 
 setup(
     name='extract_cp',
-    version='1.1.0',
+    version='1.2.0',
     description='Fetal brain MRI CP surface extraction using CIVET marching-cubes',
     author='Jennings Zhang',
     author_email='[email protected]',
     url='https://github.com/FNNDSC/pl-fetal-cp-surface-extract',
     packages=['extract_cp'],
-    install_requires=['chris_plugin'],
+    install_requires=['chris_plugin', 'loguru', 'pycivet'],
     license='MIT',
-    python_requires='>=3.10.4',
     entry_points={
         'console_scripts': [
             'extract_cp = extract_cp.__main__:main'