Fix missing channels dimension in normalization

InnerEye/ML/photometric_normalization.py

@@ -83,6 +83,10 @@ def transform(self, image: Union[np.ndarray, torch.Tensor],
  else:
  mask = np.ones_like(image)
 
+ is3d = image.ndim == 3
+ if is3d:
+ image = image[np.newaxis]
+
  self.status_of_most_recent_call = None
  if self.norm_method == PhotometricNormalizationMethod.Unchanged:
  image_out = image
@@ -117,6 +121,9 @@ def transform(self, image: Union[np.ndarray, torch.Tensor],
  logging.debug(f"Photonorm patient {patient_id}: {self.status_of_most_recent_call}")
  check_array_range(image_out, error_prefix="Normalized image")
 
+ if is3d:
+ image_out = image_out[0]
+
  return image_out