Add interpolator parameter with sitkBSpline as default

Author: MaxenceLarose

delia/transforms/physical_space/matching_resample.py

@@ -8,11 +8,11 @@
     @Description:       This file contains the MatchingResampled transform.
 """
 
-from typing import Dict, Hashable
+from typing import Callable, Dict, Hashable
 
 import SimpleITK as sitk
 
-from delia.transforms.physical_space.transform import PhysicalSpaceTransform, ImageData, KeysCollection
+from delia.transforms.physical_space.transform import PhysicalSpaceTransform, ImageData, KeysCollection, Mode
 
 
 class MatchingResampled(PhysicalSpaceTransform):
@@ -24,6 +24,7 @@ def __init__(
             self,
             reference_image_key: str,
             matching_keys: KeysCollection,
+            interpolator: Callable = sitk.sitkBSpline,
     ):
         """
         Initializes images.
@@ -37,10 +38,13 @@ def __init__(
             for foreground on the image. Image keys are assumed to be arbitrary series keys defined in
             'series_descriptions'. For the label maps, the keys are organ names. Note that if 'series_descriptions' is
             None, the image keys are assumed to be modality names.
+        interpolator : Callable
+            The interpolator to be used for resampling the images. Default = sitk.sitkBSpline.
         """
         keys = [key for key in matching_keys] + [reference_image_key]
         super().__init__(keys=keys)
         self._reference_image_key = reference_image_key
+        self._interpolator = interpolator
 
     def __call__(self, data: Dict[str, ImageData]) -> Dict[Hashable, sitk.Image]:
         """
@@ -65,7 +69,21 @@ def __call__(self, data: Dict[str, ImageData]) -> Dict[Hashable, sitk.Image]:
 
         for key in self.key_iterator(d):
             if key != self._reference_image_key:
-                d[key] = sitk.Resample(d[key].simple_itk_image, reference_image)
+
+                if self._mode == Mode.NONE:
+                    raise AssertionError("Transform mode must be set before __call__.")
+                elif self._mode == Mode.IMAGE:
+                    interpolator = self._interpolator
+                elif self._mode == Mode.SEGMENTATION:
+                    interpolator = sitk.sitkNearestNeighbor
+                else:
+                    raise ValueError("Unknown transform mode.")
+
+                d[key] = sitk.Resample(
+                    image1=d[key].simple_itk_image,
+                    referenceImage=reference_image,
+                    interpolator=interpolator
+                )
 
         return d
 

delia/transforms/physical_space/resample.py

@@ -8,7 +8,7 @@
     @Description:       This file contains the Resampled transform.
 """
 
-from typing import Dict, Hashable, Tuple
+from typing import Callable, Dict, Hashable, Tuple
 
 import SimpleITK as sitk
 import numpy as np
@@ -24,7 +24,8 @@ class Resampled(PhysicalSpaceTransform):
     def __init__(
             self,
             keys: KeysCollection,
-            out_spacing: Tuple[float, float, float] = (1.0, 1.0, 1.0)
+            out_spacing: Tuple[float, float, float] = (1.0, 1.0, 1.0),
+            interpolator: Callable = sitk.sitkBSpline,
     ):
         """
         Initialize output spacing.
@@ -37,9 +38,12 @@ def __init__(
             'series_descriptions' is None, the image keys are assumed to be modality names.
         out_spacing : Tuple[int, int, int], default = (1.0, 1.0, 1.0)
             The desired spacing in the physical space. Default = (1.0 mm, 1.0 mm, 1.0 mm).
+        interpolator : Callable
+            The interpolator to be used for resampling the images. Default = sitk.sitkBSpline.
         """
         super().__init__(keys=keys)
         self._out_spacing = out_spacing
+        self._interpolator = interpolator
 
     def __call__(self, data: Dict[str, ImageData]) -> Dict[Hashable, sitk.Image]:
         """
@@ -80,7 +84,7 @@ def __call__(self, data: Dict[str, ImageData]) -> Dict[Hashable, sitk.Image]:
             if self._mode == Mode.NONE:
                 raise AssertionError("Transform mode must be set before __call__.")
             elif self._mode == Mode.IMAGE:
-                resample.SetInterpolator(sitk.sitkLinear)
+                resample.SetInterpolator(self._interpolator)
             elif self._mode == Mode.SEGMENTATION:
                 resample.SetInterpolator(sitk.sitkNearestNeighbor)
             else: