diff --git a/src/eva/vision/data/datasets/segmentation/total_segmentator_2d.py b/src/eva/vision/data/datasets/segmentation/total_segmentator_2d.py
index 7903a06f..20fc2a1b 100644
--- a/src/eva/vision/data/datasets/segmentation/total_segmentator_2d.py
+++ b/src/eva/vision/data/datasets/segmentation/total_segmentator_2d.py
@@ -184,21 +184,21 @@ def validate(self) -> None:
             return
 
         if self._classes:
-            first_and_last_labels = (self._classes[0], self._classes[-1])
+            last_label = self._classes[-1]
             n_classes = len(self._classes)
         elif self._class_mappings:
             classes = sorted(set(self._class_mappings.values()))
-            first_and_last_labels = (classes[0], classes[-1])
+            last_label = classes[-1]
             n_classes = len(classes)
         else:
-            first_and_last_labels = ("adrenal_gland_left", "vertebrae_T9")
+            last_label = "vertebrae_T9"
             n_classes = 117
 
         _validators.check_dataset_integrity(
             self,
             length=self._expected_dataset_lengths.get(f"{self._split}_{self._version}", 0),
-            n_classes=n_classes+1,
-            first_and_last_labels=first_and_last_labels,
+            n_classes=n_classes + 1,
+            first_and_last_labels=("background", last_label),
         )
 
     @override
@@ -250,11 +250,9 @@ def _load_masks_as_semantic_label(
         binary_masks = [io.read_nifti(path, slice_index) for path in mask_paths]
 
         if self._class_mappings:
-            mapped_binary_masks = [np.zeros_like(binary_masks[0], dtype=np.bool_)] * len(
-                self.classes
-            )
+            mapped_binary_masks = [np.zeros_like(binary_masks[0], dtype=np.bool_)] * len(self.classes[1:])
             for original_class, mapped_class in self._class_mappings.items():
-                mapped_index = self.class_to_idx[mapped_class]
+                mapped_index = self.class_to_idx[mapped_class] - 1
                 original_index = list(self._class_mappings.keys()).index(original_class)
                 mapped_binary_masks[mapped_index] = np.logical_or(
                     mapped_binary_masks[mapped_index], binary_masks[original_index]