diff --git a/src/mednet/libs/segmentation/engine/evaluator.py b/src/mednet/libs/segmentation/engine/evaluator.py
index 6da6282c6758ddb4948a5f622839c343100afc0d..5f947b5df568e8d9eafe476f192bc6f23fb2f187 100644
--- a/src/mednet/libs/segmentation/engine/evaluator.py
+++ b/src/mednet/libs/segmentation/engine/evaluator.py
@@ -364,7 +364,7 @@ def _evaluate_sample_worker(
     retval = _sample_measures(prediction, target, mask, steps)
 
     if output_folder is not None:
-        fullpath = output_folder / name / f"{pathlib.Path(stem).stem}.csv"
+        fullpath = (output_folder / name / f"{stem}").with_suffix(".csv")
         tqdm.write(f"Saving {fullpath}...")
         fullpath.parent.mkdir(parents=True, exist_ok=True)
         retval.to_csv(fullpath)
diff --git a/src/mednet/libs/segmentation/scripts/predict.py b/src/mednet/libs/segmentation/scripts/predict.py
index 023b016258561cb30b698df0eb1fef89754383db..04b3d57d6c216d41361d256e91b93130399158e9 100644
--- a/src/mednet/libs/segmentation/scripts/predict.py
+++ b/src/mednet/libs/segmentation/scripts/predict.py
@@ -116,7 +116,7 @@ def predict(
     for split_name, split in predictions.items():
         pred_paths = []
         for sample in split:
-            hdf5_path = output_folder / f"{pathlib.Path(sample[0]).stem}.hdf5"
+            hdf5_path = (output_folder / f"{sample[0]}").with_suffix(".hdf5")
             _save_hdf5(sample[3], sample[1], sample[2], hdf5_path)
             pred_paths.append([str(sample[0]), str(hdf5_path)])
         json_predictions[split_name] = pred_paths