docs/changes/newsfragments/284.bugfix

@@ -0,0 +1 @@
+Avoid warping mask preprocessed with :class:`.fMRIPrepConfoundRemover` and used by markers with ``mask="inherit"`` in subject-native template space by `Fede Raimondo`_ and `Synchon Mandal`_

junifer/data/masks.py

@@ -280,12 +280,16 @@ def get_mask(  # noqa: C901
                     f"because the item ({inherited_mask_item}) does not exist."
                 )
             mask_img = extra_input[inherited_mask_item]["data"]
+            mask_space = target_data["space"]
         # Starting with new mask
         else:
             # Load mask
             mask_object, _, mask_space = load_mask(
                 mask_name, path_only=False, resolution=resolution
             )
+            # Replace mask space with target space if mask's space is inherit
+            if mask_space == "inherit":
+                mask_space = target_data["space"]
             # If mask is callable like from nilearn
             if callable(mask_object):
                 if mask_params is None:
@@ -311,15 +315,17 @@ def get_mask(  # noqa: C901
 
     # Multiple masks, need intersection / union
     if len(all_masks) > 1:
-        # Filter out "inherit" and make a set for spaces
+        # Make a set of unique spaces
-        filtered_spaces = set(filter(lambda x: x != "inherit", all_spaces))
+        unique_spaces = set(all_spaces)
         # Intersect / union of masks only if all masks are in the same space
-        if len(filtered_spaces) == 1:
+        if len(unique_spaces) == 1:
             mask_img = intersect_masks(all_masks, **intersect_params)
+            # Store the mask space for further checks
+            mask_space = next(iter(unique_spaces))
         else:
             raise_error(
                 msg=(
-                    f"Masks are in different spaces: {filtered_spaces}, "
+                    f"Masks are in different spaces: {unique_spaces}, "
                     "unable to merge."
                 ),
                 klass=RuntimeError,
@@ -333,9 +339,10 @@ def get_mask(  # noqa: C901
                 "when there is only one mask."
             )
         mask_img = all_masks[0]
+        mask_space = all_spaces[0]
 
-    # Warp mask if target data is native
+    # Warp mask if target data is native and mask space is not native
-    if target_data["space"] == "native":
+    if target_data["space"] == "native" and target_data["space"] != mask_space:
         # Check for extra inputs
         if extra_input is None:
             raise_error(

junifer/data/tests/test_masks.py

@@ -392,7 +392,9 @@ def test_get_mask_inherit() -> None:
 
         # Now get the mask using the inherit functionality, passing the
         # computed mask as extra data
-        extra_input = {"BOLD_MASK": {"data": gm_mask}}
+        extra_input = {
+            "BOLD_MASK": {"data": gm_mask, "space": input["BOLD"]["space"]}
+        }
         input["BOLD"]["mask_item"] = "BOLD_MASK"
         mask2 = get_mask(
             masks="inherit", target_data=input["BOLD"], extra_input=extra_input
@@ -405,11 +407,9 @@ def test_get_mask_inherit() -> None:
 @pytest.mark.parametrize(
     "masks,params",
     [
-        (["GM_prob0.2", "compute_brain_mask"], {}),
+        (["GM_prob0.2", "GM_prob0.2_cortex"], {}),
-        (
+        (["compute_brain_mask", "compute_background_mask"], {}),
-            ["GM_prob0.2", "compute_brain_mask"],
+        (["compute_brain_mask", "compute_epi_mask"], {}),
-            {"threshold": 0.2},
-        ),
     ],
 )
 def test_get_mask_multiple(

junifer/preprocess/confounds/fmriprep_confound_remover.py

@@ -574,7 +574,10 @@ class fMRIPrepConfoundRemover(BasePreprocessor):
             # this allows to use "inherit" down the pipeline
             if extra_input is not None:
                 logger.debug("Setting mask_item")
-                extra_input["BOLD_mask"] = {"data": mask_img}
+                extra_input["BOLD_mask"] = {
+                    "data": mask_img,
+                    "space": input["space"],
+                }
                 input["mask_item"] = "BOLD_mask"
 
         logger.info("Cleaning image")