diff --git a/klausur-service/backend/page_crop.py b/klausur-service/backend/page_crop.py
index 531b000..28d3fd1 100644
--- a/klausur-service/backend/page_crop.py
+++ b/klausur-service/backend/page_crop.py
@@ -201,8 +201,8 @@ def detect_and_crop_page(
     # --- Left edge: spine-shadow detection ---
     left_edge = _detect_left_edge_shadow(gray, binary, w, h)
 
-    # --- Right edge: binary vertical projection ---
-    right_edge = _detect_right_edge(binary, w, h)
+    # --- Right edge: spine-shadow detection ---
+    right_edge = _detect_right_edge_shadow(gray, binary, w, h)
 
     # --- Top / bottom edges: binary horizontal projection ---
     top_edge, bottom_edge = _detect_top_bottom_edges(binary, w, h)
@@ -323,8 +323,50 @@ def _detect_left_edge_shadow(
     return _detect_edge_projection(binary, axis=0, from_start=True, dim=w)
 
 
-def _detect_right_edge(binary: np.ndarray, w: int, h: int) -> int:
-    """Detect right content edge via binary vertical projection."""
+def _detect_right_edge_shadow(
+    gray: np.ndarray,
+    binary: np.ndarray,
+    w: int,
+    h: int,
+) -> int:
+    """Detect right content edge, accounting for book-spine shadow.
+
+    Mirror of _detect_left_edge_shadow: look at the right 25% of the image
+    for a brightness dip (scanner gray strip at book spine).
+    The darkest point in the gradient marks the spine center; crop there.
+    """
+    search_w = max(1, w // 4)
+    right_start = w - search_w
+
+    # Column-mean brightness in the right quarter
+    col_means = np.mean(gray[:, right_start:], axis=0).astype(np.float64)
+
+    # Smooth with boxcar kernel (width = 1% of image width, min 5)
+    kernel_size = max(5, w // 100)
+    if kernel_size % 2 == 0:
+        kernel_size += 1
+    kernel = np.ones(kernel_size) / kernel_size
+    smoothed = np.convolve(col_means, kernel, mode="same")
+
+    # Determine brightness threshold: midpoint between darkest and brightest
+    val_min = float(np.min(smoothed))
+    val_max = float(np.max(smoothed))
+    shadow_range = val_max - val_min
+
+    # Only use shadow detection if there is a meaningful brightness gradient (> 20 levels)
+    if shadow_range > 20:
+        threshold = val_min + shadow_range * 0.6
+        # Find LAST column (from right) where brightness exceeds threshold
+        # = first column from right that drops below threshold marks the spine
+        above = np.where(smoothed >= threshold)[0]
+        if len(above) > 0:
+            # The last bright column before it drops into shadow
+            shadow_edge = right_start + int(above[-1])
+            logger.debug("Right edge: shadow detected at x=%d (range=%.0f)",
+                         shadow_edge, shadow_range)
+            return shadow_edge
+
+    # Fallback: binary vertical projection
     return _detect_edge_projection(binary, axis=0, from_start=False, dim=w)