diff --git a/tests/test_imagewrapper.py b/tests/test_imagewrapper.py
index c481ada3158b475846ba7bd17d57a4f91abf2297..b074358d28f6ee05101fa4e7a9a714249c7820dc 100644
--- a/tests/test_imagewrapper.py
+++ b/tests/test_imagewrapper.py
@@ -9,14 +9,12 @@ from __future__ import print_function
 
 import              collections
 import              random
-import              time
 import itertools as it
 import numpy     as np
 import nibabel   as nib
 import              pytest
 
-
-import fsl.data.image        as image
+import fsl.utils.naninfrange as nir
 import fsl.data.imagewrapper as imagewrap
 
 from . import random_voxels
@@ -291,46 +289,6 @@ def test_sliceTupleToSliceObj():
             assert func(slices) == sliceobj
 
 
-def test_naninfrange():
-    # numinf, numnan, expectedResult
-    tests = [( 0,     0,    (0,      100)),
-             ( 0,     1,    (0,      100)),
-             ( 1,     0,    (0,      100)),
-             ( 1,     1,    (0,      100)),
-             ( 5,     5,    (0,      100)),
-             ( 0,    'all', (np.nan, np.nan)),
-             ('all',  0,    (np.nan, np.nan))]
-
-    # Test non floating point data as wll
-    data = np.linspace(0, 100, 100, dtype=np.uint32)
-    assert imagewrap.naninfrange(data) == (0, 100)
-
-    for numinf, numnan, expected in tests:
-
-        data   = np.linspace(0, 100, 100)
-
-        if   numinf == 'all': data[:] = np.inf
-        elif numnan == 'all': data[:] = np.nan
-
-        nanoff = 1
-        if numinf != 'all':
-            for i in range(1, numinf + 1):
-                data[i] = np.inf
-            nanoff += numinf
-
-        if numnan != 'all':
-            for i in range(nanoff, numnan + nanoff):
-                data[i] = np.nan
-
-        result = imagewrap.naninfrange(data)
-
-        if   np.isfinite(expected[0]): assert result[0] == expected[0]
-        elif np.isnan(   expected[0]): assert np.isnan(result[0])
-        elif np.isinf(   expected[0]): assert np.isinf(result[0])
-        if   np.isfinite(expected[1]): assert result[1] == expected[1]
-        elif np.isnan(   expected[1]): assert np.isnan(result[1])
-        elif np.isinf(   expected[1]): assert np.isinf(result[1])
-
 
 def test_adjustCoverage():
 
@@ -617,7 +575,7 @@ def _test_ImageWrapper_read(niters, seed, threaded, addnans=False):
                 data[coords] = np.nan
 
 
-        volRanges = [imagewrap.naninfrange(data[..., v]) for v in range(nvols)]
+        volRanges = [nir.naninfrange(data[..., v]) for v in range(nvols)]
 
         rrs = []
         for vol in range(nvols):
diff --git a/tests/test_naninfrange.py b/tests/test_naninfrange.py
new file mode 100644
index 0000000000000000000000000000000000000000..dee79948a1a4021ab6f0e3fa72a84e64319e5b4d
--- /dev/null
+++ b/tests/test_naninfrange.py
@@ -0,0 +1,52 @@
+#!/usr/bin/env python
+#
+# test_naninfrange.py -
+#
+# Author: Paul McCarthy <pauldmccarthy@gmail.com>
+#
+
+
+import numpy as np
+
+import fsl.utils.naninfrange as naninfrange
+
+
+def test_naninfrange():
+    # numinf, numnan, expectedResult
+    tests = [( 0,     0,    (0,      100)),
+             ( 0,     1,    (0,      100)),
+             ( 1,     0,    (0,      100)),
+             ( 1,     1,    (0,      100)),
+             ( 5,     5,    (0,      100)),
+             ( 0,    'all', (np.nan, np.nan)),
+             ('all',  0,    (np.nan, np.nan))]
+
+    # Test non floating point data as wll
+    data = np.linspace(0, 100, 100, dtype=np.uint32)
+    assert naninfrange.naninfrange(data) == (0, 100)
+
+    for numinf, numnan, expected in tests:
+
+        data   = np.linspace(0, 100, 100)
+
+        if   numinf == 'all': data[:] = np.inf
+        elif numnan == 'all': data[:] = np.nan
+
+        nanoff = 1
+        if numinf != 'all':
+            for i in range(1, numinf + 1):
+                data[i] = np.inf
+            nanoff += numinf
+
+        if numnan != 'all':
+            for i in range(nanoff, numnan + nanoff):
+                data[i] = np.nan
+
+        result = naninfrange.naninfrange(data)
+
+        if   np.isfinite(expected[0]): assert result[0] == expected[0]
+        elif np.isnan(   expected[0]): assert np.isnan(result[0])
+        elif np.isinf(   expected[0]): assert np.isinf(result[0])
+        if   np.isfinite(expected[1]): assert result[1] == expected[1]
+        elif np.isnan(   expected[1]): assert np.isnan(result[1])
+        elif np.isinf(   expected[1]): assert np.isinf(result[1])