diff --git a/scilpy/io/image.py b/scilpy/io/image.py
index 727e9b4a2..f2739d38d 100644
--- a/scilpy/io/image.py
+++ b/scilpy/io/image.py
@@ -2,9 +2,35 @@
 
 from dipy.io.utils import is_header_compatible
 import logging
+import nibabel as nib
 import numpy as np
 import os
 
+from scilpy.utils.util import is_float
+
+
+def load_img(arg):
+    if is_float(arg):
+        img = float(arg)
+        dtype = np.float64
+    else:
+        if not os.path.isfile(arg):
+            raise ValueError('Input file {} does not exist.'.format(arg))
+        img = nib.load(arg)
+        shape = img.header.get_data_shape()
+        dtype = img.header.get_data_dtype()
+        logging.info('Loaded {} of shape {} and data_type {}.'.format(
+                     arg, shape, dtype))
+
+        if len(shape) > 3:
+            logging.warning('{} has {} dimensions, be careful.'.format(
+                arg, len(shape)))
+        elif len(shape) < 3:
+            raise ValueError('{} has {} dimensions, not valid.'.format(
+                arg, len(shape)))
+
+    return img, dtype
+
 
 def merge_labels_into_mask(atlas, filtering_args):
     """
diff --git a/scripts/scil_image_math.py b/scripts/scil_image_math.py
index 4819280c7..508380a66 100755
--- a/scripts/scil_image_math.py
+++ b/scripts/scil_image_math.py
@@ -22,6 +22,7 @@
 import numpy as np
 
 from scilpy.image.volume_math import (get_image_ops, get_operations_doc)
+from scilpy.io.image import load_img
 from scilpy.io.utils import (add_overwrite_arg,
                              add_verbose_arg,
                              assert_outputs_exist)
@@ -59,29 +60,6 @@ def _build_arg_parser():
     return p
 
 
-def load_img(arg):
-    if is_float(arg):
-        img = float(arg)
-        dtype = np.float64
-    else:
-        if not os.path.isfile(arg):
-            raise ValueError('Input file {} does not exist.'.format(arg))
-        img = nib.load(arg)
-        shape = img.header.get_data_shape()
-        dtype = img.header.get_data_dtype()
-        logging.info('Loaded {} of shape {} and data_type {}.'.format(
-                     arg, shape, dtype))
-
-        if len(shape) > 3:
-            logging.warning('{} has {} dimensions, be careful.'.format(
-                arg, len(shape)))
-        elif len(shape) < 3:
-            raise ValueError('{} has {} dimensions, not valid.'.format(
-                arg, len(shape)))
-
-    return img, dtype
-
-
 def main():
     parser = _build_arg_parser()
     args = parser.parse_args()