diff --git a/src/ptbench/configs/datasets/tbx11k_simplified/__init__.py b/src/ptbench/configs/datasets/tbx11k_simplified/__init__.py
index 277fd087148c1c989b49a0766e51325aaf0a34e6..f52f2db110f7ca533d32e300f2309ffab3f14584 100644
--- a/src/ptbench/configs/datasets/tbx11k_simplified/__init__.py
+++ b/src/ptbench/configs/datasets/tbx11k_simplified/__init__.py
@@ -19,7 +19,7 @@ def _maker(protocol, RGB=False):
 
     return mk(
         [raw.subsets(protocol)],
-        [RGBtoGreyscale8bit()],
+        [],
         [ElasticDeformation(p=0.8)],
         post_transforms,
     )
diff --git a/src/ptbench/data/transforms.py b/src/ptbench/data/transforms.py
index 031bde8912a111039f3e103b278fa04f7b82249c..c1f1f7d0a4457fb441ddfefa5bd53c9e57bd2a60 100644
--- a/src/ptbench/data/transforms.py
+++ b/src/ptbench/data/transforms.py
@@ -42,39 +42,6 @@ class SingleAutoLevel16to8:
         ).convert("L")
 
 
-class RGBtoGreyscale8bit:
-    """Converts a 24-bit RGB image to an 8-bit greyscale representation.
-
-    This transform assumes that the input image is RGB with 24 bits.
-
-    Converts the RGB image to a greyscale image using the well-known formula:
-    Y = 0.299 * R + 0.587 * G + 0.114 * B
-    This formula is based on the relative luminance of the RGB channels in the sRGB color space
-
-    consider such a range should be mapped to the [0,255] range of the
-    destination image.
-    """
-
-    def __call__(self, img):
-        # Use the formula to convert the RGB image to a greyscale image
-        img_array = numpy.array(img).astype(float)
-        grey_array = (
-            0.299 * img_array[:, :, 0]
-            + 0.587 * img_array[:, :, 1]
-            + 0.114 * img_array[:, :, 2]
-        )
-
-        # Normalize the greyscale image to the range [0, 255] and convert it to uint8
-        grey_array = numpy.round(
-            255.0
-            * (grey_array - grey_array.min())
-            / (grey_array.max() - grey_array.min())
-        ).astype("uint8")
-
-        # Create a new greyscale PIL image from the normalized array
-        return PIL.Image.fromarray(grey_array).convert("L")
-
-
 class RemoveBlackBorders:
     """Remove black borders of CXR."""