Update app.py

app.py

@@ -105,26 +105,26 @@ WINDOW_WIDTH_MAX = 3000
 # Evaluation Transforms
 eval_transforms = Compose(
     [
-        LoadImage(image_only=True), 
+        LoadImage(image_only=True, reader="ITKReader"), 
         AsChannelFirst(), 
         ScaleIntensityRangePercentiles(lower=20, upper=80, b_min=0.0, b_max=1.0, clip=False, relative=True), 
         Resize(spatial_size=SPATIAL_SIZE)
     ]
 )
 
-# CAM Original Transforms
-cam_original_transforms = Compose(
+# CAM Transforms
+cam_transforms = Compose(
     [
-        LoadImage(image_only=True), 
+        LoadImage(image_only=True, reader="ITKReader"), 
         AsChannelFirst(), 
         Resize(spatial_size=SPATIAL_SIZE)
     ]
 )
 
-# CAM Original Transforms
+# Original Transforms
 original_transforms = Compose(
     [
-        LoadImage(image_only=True), 
+        LoadImage(image_only=True, reader="ITKReader"), 
         AsChannelFirst()
     ]
 )
@@ -210,7 +210,7 @@ if uploaded_ct_file is not None:
         )
 
         # Load the original DICOM image for display
-        display_image_tensor = cam_original_transforms(temp_file.name).unsqueeze(0).to(device)
+        display_image_tensor = cam_transforms(temp_file.name).unsqueeze(0).to(device)
         display_image = display_image_tensor.squeeze()
 
         # Transform the image and apply windowing
@@ -277,7 +277,7 @@ if uploaded_mri_file is not None:
         )
 
         # Load the original DICOM image for display
-        display_image_tensor = cam_original_transforms(temp_file.name).unsqueeze(0).to(device)
+        display_image_tensor = cam_transforms(temp_file.name).unsqueeze(0).to(device)
         display_image = display_image_tensor.squeeze()
 
         # Transform the image and apply windowing