diff --git a/tests/test_transforms.py b/tests/test_transforms.py
index a8f1d71479c7c954c7459f6b85ddbb0d00e0bef5..33e80bb9a8fe30cbacbd1241e65b7ee9694846a8 100644
--- a/tests/test_transforms.py
+++ b/tests/test_transforms.py
@@ -8,10 +8,7 @@ import PIL.Image
 import torch
 import torchvision.transforms.functional as F  # noqa: N812
 from mednet.libs.common.data.augmentations import ElasticDeformation
-from mednet.libs.common.models.transforms import (
-    crop_image_to_mask,
-    resize_max_side,
-)
+from mednet.libs.common.models.transforms import crop_image_to_mask
 
 
 def test_crop_mask():
@@ -29,29 +26,6 @@ def test_crop_mask():
     assert torch.all(cropped_tensor.eq(tensor[slice_]))
 
 
-def test_resize_max_size():
-    original_size = (3, 50, 100)
-    original_ratio = original_size[1] / original_size[2]
-
-    new_max_side = 120
-    tensor = torch.rand(original_size)
-
-    resized_tensor = resize_max_side(tensor, new_max_side)
-    resized_ratio = resized_tensor.shape[1] / resized_tensor.shape[2]
-    assert original_ratio == resized_ratio
-
-    transposed_tensor = tensor.transpose(1, 2)
-
-    resized_transposed_tensor = resize_max_side(transposed_tensor, new_max_side)
-    inv_ratio = 1 / (
-        resized_transposed_tensor.shape[1] / resized_transposed_tensor.shape[2]
-    )
-    assert original_ratio == inv_ratio
-
-    assert resized_tensor.shape[1] == resized_transposed_tensor.shape[2]
-    assert resized_tensor.shape[2] == resized_transposed_tensor.shape[1]
-
-
 def test_elastic_deformation(datadir):
     # Get a raw sample without deformation
     data_file = str(datadir / "raw_without_elastic_deformation.png")