diff --git a/monai/transforms/utils.py b/monai/transforms/utils.py
index b1f1bbd0f6..32fffc25f0 100644
--- a/monai/transforms/utils.py
+++ b/monai/transforms/utils.py
@@ -1863,7 +1863,7 @@ class Fourier:
     """
 
     @staticmethod
-    def shift_fourier(x: NdarrayOrTensor, spatial_dims: int) -> NdarrayOrTensor:
+    def shift_fourier(x: NdarrayOrTensor, spatial_dims: int, as_contiguous: bool = False) -> NdarrayOrTensor:
         """
         Applies fourier transform and shifts the zero-frequency component to the
         center of the spectrum. Only the spatial dimensions get transformed.
@@ -1871,6 +1871,7 @@ def shift_fourier(x: NdarrayOrTensor, spatial_dims: int) -> NdarrayOrTensor:
         Args:
             x: Image to transform.
             spatial_dims: Number of spatial dimensions.
+            as_contiguous: Whether to convert the cached NumPy array or PyTorch tensor to be contiguous.
 
         Returns
             k: K-space data.
@@ -1885,10 +1886,12 @@ def shift_fourier(x: NdarrayOrTensor, spatial_dims: int) -> NdarrayOrTensor:
                 k = np.fft.fftshift(np.fft.fftn(x.cpu().numpy(), axes=dims), axes=dims)
         else:
             k = np.fft.fftshift(np.fft.fftn(x, axes=dims), axes=dims)
-        return k
+        return ascontiguousarray(k) if as_contiguous else k
 
     @staticmethod
-    def inv_shift_fourier(k: NdarrayOrTensor, spatial_dims: int, n_dims: int | None = None) -> NdarrayOrTensor:
+    def inv_shift_fourier(
+        k: NdarrayOrTensor, spatial_dims: int, n_dims: int | None = None, as_contiguous: bool = False
+    ) -> NdarrayOrTensor:
         """
         Applies inverse shift and fourier transform. Only the spatial
         dimensions are transformed.
@@ -1896,6 +1899,7 @@ def inv_shift_fourier(k: NdarrayOrTensor, spatial_dims: int, n_dims: int | None
         Args:
             k: K-space data.
             spatial_dims: Number of spatial dimensions.
+            as_contiguous: Whether to convert the cached NumPy array or PyTorch tensor to be contiguous.
 
         Returns:
             x: Tensor in image space.
@@ -1910,7 +1914,7 @@ def inv_shift_fourier(k: NdarrayOrTensor, spatial_dims: int, n_dims: int | None
                 out = np.fft.ifftn(np.fft.ifftshift(k.cpu().numpy(), axes=dims), axes=dims).real
         else:
             out = np.fft.ifftn(np.fft.ifftshift(k, axes=dims), axes=dims).real
-        return out
+        return ascontiguousarray(out) if as_contiguous else out
 
 
 def get_number_image_type_conversions(transform: Compose, test_data: Any, key: Hashable | None = None) -> int: