diff --git a/diffdrr/renderers.py b/diffdrr/renderers.py
index e26cda210..32259c825 100644
--- a/diffdrr/renderers.py
+++ b/diffdrr/renderers.py
@@ -132,10 +132,6 @@ def dims(self, volume):
     def forward(
         self, volume, spacing, source, target, n_points=100, align_corners=True
     ):
-        # Reorder array to match torch conventions
-        volume = volume.permute(2, 1, 0)
-        spacing = spacing[[2, 1, 0]]
-
         # Get the raylength and reshape sources
         raylength = (source - target + self.eps).norm(dim=-1)
         source = source[:, None, :, None, :]
@@ -147,6 +143,9 @@ def forward(
         rays = source + alphas * (target - source)
         rays = 2 * rays / (spacing * self.dims(volume)) - 1
 
+        # Reorder array to match torch conventions
+        volume = volume.permute(2, 1, 0)
+
         # Render the DRR
         batch_size = len(rays)
         vol = volume[None, None, :, :, :].expand(batch_size, -1, -1, -1, -1)
diff --git a/notebooks/api/01_renderers.ipynb b/notebooks/api/01_renderers.ipynb
index 07672e03a..f305b43f4 100644
--- a/notebooks/api/01_renderers.ipynb
+++ b/notebooks/api/01_renderers.ipynb
@@ -257,10 +257,6 @@
     "        return torch.tensor(volume.shape).to(volume) + 1\n",
     "\n",
     "    def forward(self, volume, spacing, source, target, n_points=100, align_corners=True):        \n",
-    "        # Reorder array to match torch conventions\n",
-    "        volume = volume.permute(2, 1, 0)\n",
-    "        spacing = spacing[[2, 1, 0]]\n",
-    "\n",
     "        # Get the raylength and reshape sources\n",
     "        raylength = (source - target + self.eps).norm(dim=-1)\n",
     "        source = source[:, None, :, None, :]\n",
@@ -272,6 +268,9 @@
     "        rays = source + alphas * (target - source)\n",
     "        rays = 2 * rays / (spacing * self.dims(volume)) - 1\n",
     "\n",
+    "        # Reorder array to match torch conventions\n",
+    "        volume = volume.permute(2, 1, 0)\n",
+    "        \n",
     "        # Render the DRR\n",
     "        batch_size = len(rays)\n",
     "        vol = volume[None, None, :, :, :].expand(batch_size, -1, -1, -1, -1)\n",