diff --git a/web_api/app/alignment.py b/web_api/app/alignment.py
index 9e90ecf81..53a109516 100644
--- a/web_api/app/alignment.py
+++ b/web_api/app/alignment.py
@@ -31,7 +31,10 @@ class CorrespondencesDict(BaseModel):
         ..., description="List of correspondence lines"
     )
 
-
+# TODO: Refactor endpoint:
+#  - receive binary blobs (json-descriptor, image-data, src-mask-data, tgt-mask-data)
+#  - decode blobs to numpy arrays
+#  - return blob files (relaxed-field-data, warped-image-data) as gzipped stream
 class ApplyCorrespondencesRequest(BaseModel):
     correspondences_dict: CorrespondencesDict = Field(
         ..., description="Dictionary with correspondence lines"
@@ -48,6 +51,16 @@ class ApplyCorrespondencesRequest(BaseModel):
     optimizer_type: str = Field(
         "adam", description="Optimizer to use (adam, lbfgs, sgd, adamw)"
     )
+    src_mask: list[list[list[list[float]]]] | None = Field(
+        None,
+        description="Binary tissue mask (1=tissue, 0=non-tissue), shape (1, H, W, 1)."
+        "Zeros break rigidity constraints between regions.",
+    )
+    tgt_mask: list[list[list[list[float]]]] | None = Field(
+        None,
+        description="Binary tissue mask (1=tissue, 0=non-tissue), shape (1, H, W, 1)."
+        "Zeros break rigidity constraints between regions.",
+    )
 
 
 class ApplyCorrespondencesResponse(BaseModel):
@@ -106,6 +119,22 @@ async def apply_correspondences(request: ApplyCorrespondencesRequest):
         device=device
     )
 
+    src_mask_tensor = None
+    if request.src_mask is not None:
+        src_mask_tensor = torch.tensor(
+            request.src_mask,
+            dtype=torch.float32,
+            device=device
+        )
+
+    tgt_mask_tensor = None
+    if request.tgt_mask is not None:
+        tgt_mask_tensor = torch.tensor(
+            request.tgt_mask,
+            dtype=torch.float32,
+            device=device
+        )
+
     relaxed_field, warped_image = apply_correspondences_to_image(
         correspondences_dict=correspondences_dict,
         image=image_tensor,
@@ -113,6 +142,8 @@ async def apply_correspondences(request: ApplyCorrespondencesRequest):
         rig=request.rig,
         lr=request.lr,
         optimizer_type=request.optimizer_type,
+        src_mask=src_mask_tensor,
+        tgt_mask=tgt_mask_tensor,
     )
 
     # Convert to numpy arrays on CPU