diff --git a/src/torchio/transforms/augmentation/intensity/random_motion.py b/src/torchio/transforms/augmentation/intensity/random_motion.py
index f00828da..7aa0b4df 100644
--- a/src/torchio/transforms/augmentation/intensity/random_motion.py
+++ b/src/torchio/transforms/augmentation/intensity/random_motion.py
@@ -224,35 +224,18 @@ def get_rigid_transforms(
     ) -> List[sitk.Euler3DTransform]:
         center_ijk = np.array(image.GetSize()) / 2
         center_lps = image.TransformContinuousIndexToPhysicalPoint(center_ijk)
-        identity = np.eye(4)
-        matrices = [identity]
+        ident_transform = sitk.Euler3DTransform()
+        ident_transform.SetCenter(center_lps)
+        transforms = [ident_transform]
         for degrees, translation in zip(degrees_params, translation_params):
             radians = np.radians(degrees).tolist()
             motion = sitk.Euler3DTransform()
             motion.SetCenter(center_lps)
             motion.SetRotation(*radians)
             motion.SetTranslation(translation.tolist())
-            motion_matrix = self.transform_to_matrix(motion)
-            matrices.append(motion_matrix)
-        transforms = [self.matrix_to_transform(m) for m in matrices]
+            transforms.append(motion)
         return transforms
 
-    @staticmethod
-    def transform_to_matrix(transform: sitk.Euler3DTransform) -> np.ndarray:
-        matrix = np.eye(4)
-        rotation = np.array(transform.GetMatrix()).reshape(3, 3)
-        matrix[:3, :3] = rotation
-        matrix[:3, 3] = transform.GetTranslation()
-        return matrix
-
-    @staticmethod
-    def matrix_to_transform(matrix: np.ndarray) -> sitk.Euler3DTransform:
-        transform = sitk.Euler3DTransform()
-        rotation = matrix[:3, :3].flatten().tolist()
-        transform.SetMatrix(rotation)
-        transform.SetTranslation(matrix[:3, 3])
-        return transform
-
     def resample_images(
         self,
         image: sitk.Image,
@@ -261,10 +244,10 @@ def resample_images(
     ) -> List[sitk.Image]:
         floating = reference = image
         default_value = np.float64(sitk.GetArrayViewFromImage(image).min())
+        interpolator = self.get_sitk_interpolator(interpolation)
         transforms = transforms[1:]  # first is identity
         images = [image]  # first is identity
         for transform in transforms:
-            interpolator = self.get_sitk_interpolator(interpolation)
             resampler = sitk.ResampleImageFilter()
             resampler.SetInterpolator(interpolator)
             resampler.SetReferenceImage(reference)
@@ -301,7 +284,7 @@ def add_artifact(
             spectra.append(spectrum)
         self.sort_spectra(spectra, times)
         result_spectrum = torch.empty_like(spectra[0])
-        last_index = result_spectrum.shape[2]
+        last_index = result_spectrum.shape[axis]
         indices = (last_index * times).astype(int).tolist()
         indices.append(last_index)
         ini = 0