diff --git a/ants/core/ants_image_io.py b/ants/core/ants_image_io.py
index c88c5ac9..70d766f3 100644
--- a/ants/core/ants_image_io.py
+++ b/ants/core/ants_image_io.py
@@ -99,7 +99,8 @@ def from_numpy(
     if best_dtype != data.dtype:
         data = data.astype(best_dtype)
 
-    img = _from_numpy(data.T.copy(), origin, spacing, direction, has_components, is_rgb)
+    # Be explicit about ordering of data - needs to be C-contiguous
+    img = _from_numpy(data.T.copy(order='C'), origin, spacing, direction, has_components, is_rgb)
     return img
 
 
diff --git a/src/itkPyBuffer.hxx b/src/itkPyBuffer.hxx
index a1a135c7..df9717a9 100644
--- a/src/itkPyBuffer.hxx
+++ b/src/itkPyBuffer.hxx
@@ -80,7 +80,6 @@ PyBuffer<TImage>
   memset(&pyBuffer, 0, sizeof(Py_buffer));
 
   SizeType size;
-  SizeType sizeFortran;
   SizeValueType numberOfPixels = 1;
 
   const void *                buffer;
@@ -114,16 +113,9 @@ PyBuffer<TImage>
     {
     item = PySequence_Fast_GET_ITEM(shapeseq,i);
     size[i] = (SizeValueType)PyLong_AsLong(item);
-    sizeFortran[dimension - 1 - i] = (SizeValueType)PyLong_AsLong(item);
     numberOfPixels *= size[i];
     }
 
-  bool isFortranContiguous = false;
-  if( pyBuffer.strides != NULL && pyBuffer.itemsize == pyBuffer.strides[0] )
-    {
-    isFortranContiguous = true;
-    }
-
   len = numberOfPixels*numberOfComponents*pixelSize;
   if ( bufferLength != len )
     {
@@ -139,14 +131,6 @@ PyBuffer<TImage>
   RegionType region;
   region.SetIndex( start );
   region.SetSize( size );
-  if( isFortranContiguous )
-    {
-    region.SetSize( sizeFortran );
-    }
-  else
-    {
-    region.SetSize( size );
-    }
 
   PointType origin;
   origin.Fill( 0.0 );
diff --git a/src/readImage.cxx b/src/readImage.cxx
index 963ffe58..bdacc2b0 100644
--- a/src/readImage.cxx
+++ b/src/readImage.cxx
@@ -36,7 +36,13 @@ AntsImage<ImageType> imageRead( std::string filename )
     return myImage;
 }
 
-
+/**
+ * Create an ANTsImage from a numpy array
+ *
+ * The data array must be C-contiguous, and ordered correctly
+ * See "4.1.7 Importing Image Data from a Buffer"
+ * https://itk.org/ITKSoftwareGuide/html/Book1/ITKSoftwareGuide-Book1ch4.html
+ */
 template <typename ImageType>
 AntsImage<ImageType> fromNumpy( nb::ndarray<nb::numpy> data, nb::tuple datashape )
 {
diff --git a/tests/test_core_ants_image_io.py b/tests/test_core_ants_image_io.py
index 2718e0dc..7af62863 100644
--- a/tests/test_core_ants_image_io.py
+++ b/tests/test_core_ants_image_io.py
@@ -350,5 +350,27 @@ def test_image_read_write(self):
             ants.image_read(tmpfile)
 
 
+    def test_image_from_numpy_shape(self):
+        arr = np.random.randn(1,9,1).astype('float32')
+        img = ants.from_numpy(arr)
+        self.assertEqual(img.shape, arr.shape)
+        nptest.assert_allclose(img.numpy(), arr)
+
+        arr = np.random.randn(2,3,4).astype('float32')
+        img = ants.from_numpy(arr)
+        self.assertEqual(img.shape, arr.shape)
+        nptest.assert_allclose(img.numpy(), arr)
+
+        # Test special case where shape is (1,N), was getting transposed
+        arr = np.random.randn(1,9).astype('float32')
+        img = ants.from_numpy(arr)
+        self.assertEqual(img.shape, arr.shape)
+        nptest.assert_allclose(img.numpy(), arr)
+
+        arr = np.random.randn(9,1).astype('float32')
+        img = ants.from_numpy(arr)
+        self.assertEqual(img.shape, arr.shape)
+        nptest.assert_allclose(img.numpy(), arr)
+
 if __name__ == '__main__':
     run_tests()