diff --git a/comfy_extras/nodes_fresca.py b/comfy_extras/nodes_fresca.py
index b0b86f23..fa573299 100644
--- a/comfy_extras/nodes_fresca.py
+++ b/comfy_extras/nodes_fresca.py
@@ -26,19 +26,17 @@ def Fourier_filter(x, scale_low=1.0, scale_high=1.5, freq_cutoff=20):
     x_freq = fft.fftn(x, dim=(-2, -1))
     x_freq = fft.fftshift(x_freq, dim=(-2, -1))
 
-    # 2) Create a mask to scale frequencies differently
-    B, C, H, W = x_freq.shape
-    crow, ccol = H // 2, W // 2
-
     # Initialize mask with high-frequency scaling factor
-    mask = torch.ones((B, C, H, W), device=device) * scale_high
+    mask = torch.ones(x_freq.shape, device=device) * scale_high
+    m = mask
+    for d in range(len(x_freq.shape) - 2):
+        dim = d + 2
+        cc = x_freq.shape[dim] // 2
+        f_c = min(freq_cutoff, cc)
+        m = m.narrow(dim, cc - f_c, f_c * 2)
 
     # Apply low-frequency scaling factor to center region
-    mask[
-        ...,
-        crow - freq_cutoff : crow + freq_cutoff,
-        ccol - freq_cutoff : ccol + freq_cutoff,
-    ] = scale_low
+    m[:] = scale_low
 
     # 3) Apply frequency-specific scaling
     x_freq = x_freq * mask