Merge pull request #457 from ANTsX/n4SplineDefault

ENH: default n3 / n4 spline mesh size of 1
ANTsX · Apr 25, 2023 · e48677c · e48677c
2 parents cd808ed + 87dd109
commit e48677c
Showing 1 changed file with 9 additions and 4 deletions.
diff --git a/ants/utils/bias_correction.py b/ants/utils/bias_correction.py
@@ -46,7 +46,7 @@ def n3_bias_field_correction2(
     rescale_intensities=False,
     shrink_factor=4,
     convergence={"iters": 50, "tol": 1e-7},
-    spline_param=200,
+    spline_param=None,
     number_of_fitting_levels=4,
     return_bias_field=False,
     verbose=False,
@@ -84,7 +84,7 @@ def n3_bias_field_correction2(
     spline_param : float or vector Parameter controlling number of control
         points in spline. Either single value, indicating the spacing in each
         direction, or vector with one entry per dimension of image, indicating
-        the mesh size.
+        the mesh size. If None, defaults to mesh size of 1 in all dimensions.
 
     number_of_fitting_levels : integer
         Number of fitting levels per iteration.
@@ -113,6 +113,8 @@ def n3_bias_field_correction2(
     tol = convergence["tol"]
     if mask is None:
         mask = get_mask(image)
+    if spline_param is None:
+        spline_param = [1] * image.dimension
 
     N3_CONVERGENCE_1 = "[%i,%.10f]" % (iters, tol)
     N3_SHRINK_FACTOR_1 = str(shrink_factor)
@@ -164,7 +166,7 @@ def n4_bias_field_correction(
     rescale_intensities=False,
     shrink_factor=4,
     convergence={"iters": [50, 50, 50, 50], "tol": 1e-7},
-    spline_param=200,
+    spline_param=None,
     return_bias_field=False,
     verbose=False,
     weight_mask=None,
@@ -201,7 +203,8 @@ def n4_bias_field_correction(
     spline_param : float or vector
         Parameter controlling number of control points in spline. Either single value,
         indicating the spacing in each direction, or vector with one entry per
-        dimension of image, indicating the mesh size.
+        dimension of image, indicating the mesh size. If None, defaults to mesh size of 1 in all
+        dimensions.
 
     return_bias_field : boolean
         Return bias field instead of bias corrected image.
@@ -227,6 +230,8 @@ def n4_bias_field_correction(
     tol = convergence["tol"]
     if mask is None:
         mask = get_mask(image)
+    if spline_param is None:
+        spline_param = [1] * image.dimension
 
     N4_CONVERGENCE_1 = "[%s, %.10f]" % ("x".join([str(it) for it in iters]), tol)
     N4_SHRINK_FACTOR_1 = str(shrink_factor)