Change interpolation defaults to "linear"

brainles_preprocessing/modality.py

@@ -239,6 +239,7 @@ def register(
         registration_dir: Union[str, Path],
         moving_image_name: str,
         step: PreprocessorSteps,
+        interpolator: Optional[str] = None,
     ) -> Path:
         """
         Register the current modality to a fixed image using the specified registrator.
@@ -249,9 +250,13 @@ def register(
             registration_dir (str or Path): Directory to store registration results.
             moving_image_name (str): Name of the moving image.
             step (PreprocessorSteps): The current preprocessing step.
+            interpolator (Optional[str]): Interpolation method used during registration. Only supported by ANTsRegistrator; omit it for other registrators to use the backend default.
 
         Returns:
             Path: Path to the registration matrix.
+
+        Raises:
+            ValueError: If an interpolator is passed for a registrator other than ANTsRegistrator.
         """
         fixed_image_path = Path(fixed_image_path)
         registration_dir = Path(registration_dir)
@@ -262,12 +267,21 @@ def register(
         # Note, add file ending depending on registration backend!
         registered_matrix = registration_dir / f"M_{moving_image_name}"
 
+        if interpolator is not None and not isinstance(registrator, ANTsRegistrator):
+            raise ValueError(
+                f"'interpolator' is only supported by ANTsRegistrator for registration, "
+                f"got {type(registrator).__name__}. Omit it to use the backend default."
+            )
+
+        interpolator_kwargs = {"interpolator": interpolator} if interpolator else {}
+
         registrator.register(
             fixed_image_path=fixed_image_path,
             moving_image_path=self.current,
             transformed_image_path=registered,
             matrix_path=registered_matrix,
             log_file_path=str(registered_log),
+            **interpolator_kwargs,
         )
         self.current = registered
         self.steps[step] = registered
@@ -364,6 +378,7 @@ def transform(
         moving_image_name: str,
         transformation_matrix_path: Union[str, Path],
         step: PreprocessorSteps,
+        interpolator: Optional[str] = None,
     ) -> None:
         """
         Transform the current modality using the specified registrator and transformation matrix.
@@ -375,6 +390,7 @@ def transform(
             moving_image_name (str): Name of the moving image.
             transformation_matrix_path (str or Path): Path to the transformation matrix.
             step (PreprocessorSteps): The current preprocessing step.
+            interpolator (Optional[str]): Interpolation method used during transformation. Available options depend on the chosen registrator.
         Returns:
             None
         """
@@ -385,6 +401,8 @@ def transform(
         transformed = registration_dir_path / f"{moving_image_name}.nii.gz"
         transformed_log = registration_dir_path / f"{moving_image_name}.log"
 
+        interpolator_kwargs = {"interpolator": interpolator} if interpolator else {}
+
         if (
             isinstance(registrator, (ANTsRegistrator, NiftyRegRegistrator))
             and step == PreprocessorSteps.ATLAS_REGISTERED
@@ -406,6 +424,7 @@ def transform(
                     transformation_matrix_path,  # atlas registration matrix
                 ],
                 log_file_path=str(transformed_log),
+                **interpolator_kwargs,
             )
         else:
             registrator.transform(
@@ -414,6 +433,7 @@ def transform(
                 transformed_image_path=str(transformed),
                 matrix_path=str(transformation_matrix_path),
                 log_file_path=str(transformed_log),
+                **interpolator_kwargs,
             )
 
         self.current = transformed
@@ -701,12 +721,22 @@ def deface(
                     mask_image_path=deface_mask_atlas,
                 )
 
+                if isinstance(registrator, ANTsRegistrator):
+                    nn_interpolator = "nearestNeighbor"
+                elif isinstance(registrator, NiftyRegRegistrator):
+                    nn_interpolator = "0"
+                else:
+                    raise NotImplementedError(
+                        f"Nearest-neighbour mask resampling is not configured for {type(registrator).__name__}."
+                    )
+
                 registrator.inverse_transform(
                     fixed_image_path=self.steps[PreprocessorSteps.BET],
                     moving_image_path=deface_mask_atlas,
                     transformed_image_path=mask_path,
                     matrix_path=atlas_bet_M,
                     log_file_path=defaced_dir_path / "inverse_transform.log",
+                    interpolator=nn_interpolator,
                 )
             else:
                 defacer.deface(

brainles_preprocessing/registration/ANTs/ANTs.py

@@ -61,6 +61,7 @@ def register(
         transformed_image_path: Union[str, Path],
         matrix_path: Union[str, Path],
         log_file_path: Union[str, Path],
+        interpolator: Optional[str] = None,
         **kwargs,
     ) -> None:
         """
@@ -72,6 +73,7 @@ def register(
             transformed_image_path (str or Path): Path to the transformed image (output).
             matrix_path (str or Path): Path to the transformation matrix (output).
             log_file_path (str or Path): Path to the log file.
+            interpolator (Optional[str]): Interpolator to use for the transformation. Defaults to the instantiated transformation parameters, or 'linear' if not set.
             **kwargs: Additional registration parameters to update the instantiated defaults.
 
         Raises:
@@ -123,6 +125,7 @@ def register(
             transformed_image_path=transformed_image_path,
             matrix_path=matrix_path,
             log_file_path=log_file_path,
+            interpolator=interpolator,
         )
 
         end_time = datetime.datetime.now()
@@ -148,7 +151,7 @@ def transform(
         transformed_image_path: Union[str, Path],
         matrix_path: str | Path | List[str | Path],
         log_file_path: Union[str, Path],
-        interpolator: str = "nearestNeighbor",
+        interpolator: Optional[str] = None,
         **kwargs,
     ) -> None:
         """
@@ -161,23 +164,27 @@ def transform(
             transformed_image_path (str or Path): Path to the transformed image (output).
             matrix_path (str or Path or List[str | Path]): Path to the transformation matrix or a list of matrices.
             log_file_path (str or Path): Path to the log file.
-            interpolator (str): Interpolator to use for the transformation. Default is 'nearestNeighbor'.
+            interpolator (Optional[str]): Interpolator to use for the transformation. Defaults to the instantiated transformation parameters, or 'linear' if not set.
             **kwargs: Additional transformation parameters to update the instantiated defaults.
         Raises:
             AssertionError: If the interpolator is not valid.
             FileNotFoundError: If the fixed or moving image paths do not exist.
         """
         start_time = datetime.datetime.now()
 
+        # TODO - self.transformation_params
+        # we update the transformation parameters with the provided kwargs
+        transform_kwargs = {**self.transformation_params, **kwargs}
+
+        # the interpolator argument takes precedence over the instantiated defaults
+        default_interpolator = transform_kwargs.pop("interpolator", "linear")
+        interpolator = interpolator or default_interpolator
+
         assert interpolator in VALID_INTERPOLATORS, (
             f"Invalid interpolator: {interpolator}. "
             f"Valid options are: {', '.join(VALID_INTERPOLATORS)}."
         )
 
-        # TODO - self.transformation_params
-        # we update the transformation parameters with the provided kwargs
-        transform_kwargs = {**self.transformation_params, **kwargs}
-
         # Convert all paths to Path objects
         fixed_image_path = Path(fixed_image_path)
         moving_image_path = Path(moving_image_path)
@@ -243,7 +250,7 @@ def inverse_transform(
         transformed_image_path: Union[str, Path],
         matrix_path: str | Path | List[str | Path],
         log_file_path: Union[str, Path],
-        interpolator: str = "nearestNeighbor",
+        interpolator: Optional[str] = None,
         **kwargs,
     ) -> None:
         """
@@ -255,7 +262,7 @@ def inverse_transform(
             transformed_image_path (str or Path): Path to the transformed image (output).
             matrix_path (str or Path or List[str | Path]): Path to the transformation matrix or a list of matrices.
             log_file_path (str or Path): Path to the log file.
-            interpolator (str): Interpolator to use for the transformation. Default is 'nearestNeighbor'.
+            interpolator (Optional[str]): Interpolator to use for the transformation. Defaults to the instantiated transformation parameters, or 'linear' if not set.
             **kwargs: Additional transformation parameters to update the instantiated defaults.
         """
         if not isinstance(matrix_path, list):

brainles_preprocessing/registration/niftyreg/niftyreg.py

@@ -155,7 +155,7 @@ def transform(
         transformed_image_path: str,
         matrix_path: str | Path | List[str | Path],
         log_file_path: str,
-        interpolator: str = "0",
+        interpolator: str = "1",
         **kwargs: dict,
     ) -> None:
         """
@@ -236,7 +236,7 @@ def inverse_transform(
         transformed_image_path: str,
         matrix_path: str | Path | List[str | Path],
         log_file_path: str,
-        interpolator: str = "0",
+        interpolator: str = "1",
     ) -> None:
         """
         Apply inverse transformation using NiftyReg.

brainles_preprocessing/transform.py

@@ -58,8 +58,8 @@ def apply(
                 Available options depend on the chosen registrator:
 
                 - **ANTsRegistrator**:
-                    - "linear"
-                    - "nearestNeighbor" (default)
+                    - "linear" (default)
+                    - "nearestNeighbor"
                     - "multiLabel" (deprecated, prefer "genericLabel")
                     - "gaussian"
                     - "bSpline"
@@ -70,8 +70,8 @@ def apply(
                     - "genericLabel" (recommended for label images)
 
                 - **NiftyReg**:
-                    - "0": nearest neighbor (default)
-                    - "1": linear
+                    - "0": nearest neighbor
+                    - "1": linear (default)
                     - "3": cubic spline
                     - "4": sinc