diff --git a/monai/transforms/utility/array.py b/monai/transforms/utility/array.py
index 2ed036e9a6..ae2d56a11e 100644
--- a/monai/transforms/utility/array.py
+++ b/monai/transforms/utility/array.py
@@ -127,20 +127,22 @@ class AsChannelFirst(Transform):
 
     Args:
         channel_dim: which dimension of input image is the channel, default is the last dimension.
+            if channel_dim is a sequence, the transform will move the channel dimensions to the front.
     """
 
     backend = [TransformBackends.TORCH, TransformBackends.NUMPY]
 
-    def __init__(self, channel_dim: int = -1) -> None:
-        if not (isinstance(channel_dim, int) and channel_dim >= -1):
-            raise AssertionError("invalid channel dimension.")
-        self.channel_dim = channel_dim
+    def __init__(self, channel_dim: Union[int, Sequence[int]] = -1) -> None:
+        self.channel_dim = ensure_tuple(channel_dim)
+        self.target_dim = tuple(range(len(self.channel_dim)))
 
     def __call__(self, img: NdarrayOrTensor) -> NdarrayOrTensor:
         """
         Apply the transform to `img`.
         """
-        out: NdarrayOrTensor = convert_to_tensor(moveaxis(img, self.channel_dim, 0), track_meta=get_track_meta())
+        out: NdarrayOrTensor = convert_to_tensor(
+            moveaxis(img, self.channel_dim, self.target_dim), track_meta=get_track_meta()
+        )
         return out
 
 
@@ -157,20 +159,22 @@ class AsChannelLast(Transform):
 
     Args:
         channel_dim: which dimension of input image is the channel, default is the first dimension.
+            if channel_dim is a sequence, the transform will move the channel dimensions to the back.
     """
 
     backend = [TransformBackends.TORCH, TransformBackends.NUMPY]
 
-    def __init__(self, channel_dim: int = 0) -> None:
-        if not (isinstance(channel_dim, int) and channel_dim >= -1):
-            raise AssertionError("invalid channel dimension.")
-        self.channel_dim = channel_dim
+    def __init__(self, channel_dim: Union[int, Sequence[int]] = 0) -> None:
+        self.channel_dim = ensure_tuple(channel_dim)
+        self.target_dim = tuple(range(-len(self.channel_dim), 0))
 
     def __call__(self, img: NdarrayOrTensor) -> NdarrayOrTensor:
         """
         Apply the transform to `img`.
         """
-        out: NdarrayOrTensor = convert_to_tensor(moveaxis(img, self.channel_dim, -1), track_meta=get_track_meta())
+        out: NdarrayOrTensor = convert_to_tensor(
+            moveaxis(img, self.channel_dim, self.target_dim), track_meta=get_track_meta()
+        )
         return out
 
 
diff --git a/monai/transforms/utility/dictionary.py b/monai/transforms/utility/dictionary.py
index 92eaf95d27..c948f1f530 100644
--- a/monai/transforms/utility/dictionary.py
+++ b/monai/transforms/utility/dictionary.py
@@ -218,12 +218,15 @@ class AsChannelFirstd(MapTransform):
 
     backend = AsChannelFirst.backend
 
-    def __init__(self, keys: KeysCollection, channel_dim: int = -1, allow_missing_keys: bool = False) -> None:
+    def __init__(
+        self, keys: KeysCollection, channel_dim: Union[int, Sequence[int]] = -1, allow_missing_keys: bool = False
+    ) -> None:
         """
         Args:
             keys: keys of the corresponding items to be transformed.
                 See also: :py:class:`monai.transforms.compose.MapTransform`
             channel_dim: which dimension of input image is the channel, default is the last dimension.
+                if channel_dim is a sequence, the transform will move the channel dimensions to the front.
             allow_missing_keys: don't raise exception if key is missing.
         """
         super().__init__(keys, allow_missing_keys)
@@ -243,12 +246,15 @@ class AsChannelLastd(MapTransform):
 
     backend = AsChannelLast.backend
 
-    def __init__(self, keys: KeysCollection, channel_dim: int = 0, allow_missing_keys: bool = False) -> None:
+    def __init__(
+        self, keys: KeysCollection, channel_dim: Union[int, Sequence[int]] = 0, allow_missing_keys: bool = False
+    ) -> None:
         """
         Args:
             keys: keys of the corresponding items to be transformed.
                 See also: :py:class:`monai.transforms.compose.MapTransform`
             channel_dim: which dimension of input image is the channel, default is the first dimension.
+                if channel_dim is a sequence, the transform will move the channel dimensions to the back.
             allow_missing_keys: don't raise exception if key is missing.
         """
         super().__init__(keys, allow_missing_keys)
diff --git a/tests/test_as_channel_first.py b/tests/test_as_channel_first.py
index 732c559a1a..f3a4c53de3 100644
--- a/tests/test_as_channel_first.py
+++ b/tests/test_as_channel_first.py
@@ -23,6 +23,7 @@
     TESTS.append([p, {"channel_dim": -1}, (4, 1, 2, 3)])
     TESTS.append([p, {"channel_dim": 3}, (4, 1, 2, 3)])
     TESTS.append([p, {"channel_dim": 2}, (3, 1, 2, 4)])
+    TESTS.append([p, {"channel_dim": (1, 2)}, (2, 3, 1, 4)])
 
 
 class TestAsChannelFirst(unittest.TestCase):
@@ -31,7 +32,10 @@ def test_value(self, in_type, input_param, expected_shape):
         test_data = in_type(np.random.randint(0, 2, size=[1, 2, 3, 4]))
         result = AsChannelFirst(**input_param)(test_data)
         self.assertTupleEqual(result.shape, expected_shape)
-        expected = moveaxis(test_data, input_param["channel_dim"], 0)
+        if isinstance(input_param["channel_dim"], int):
+            expected = moveaxis(test_data, input_param["channel_dim"], 0)
+        else:  # sequence
+            expected = moveaxis(test_data, input_param["channel_dim"], tuple(range(len(input_param["channel_dim"]))))
         assert_allclose(result, expected, type_test="tensor")
 
 
diff --git a/tests/test_as_channel_firstd.py b/tests/test_as_channel_firstd.py
index 91086f9299..d725e3160e 100644
--- a/tests/test_as_channel_firstd.py
+++ b/tests/test_as_channel_firstd.py
@@ -22,6 +22,7 @@
     TESTS.append([p, {"keys": ["image", "label", "extra"], "channel_dim": -1}, (4, 1, 2, 3)])
     TESTS.append([p, {"keys": ["image", "label", "extra"], "channel_dim": 3}, (4, 1, 2, 3)])
     TESTS.append([p, {"keys": ["image", "label", "extra"], "channel_dim": 2}, (3, 1, 2, 4)])
+    TESTS.append([p, {"keys": ["image", "label", "extra"], "channel_dim": (2, 3)}, (3, 4, 1, 2)])
 
 
 class TestAsChannelFirstd(unittest.TestCase):
diff --git a/tests/test_as_channel_last.py b/tests/test_as_channel_last.py
index e6446ab7a6..2c28b2259d 100644
--- a/tests/test_as_channel_last.py
+++ b/tests/test_as_channel_last.py
@@ -22,6 +22,7 @@
     TESTS.append([p, {"channel_dim": 0}, (2, 3, 4, 1)])
     TESTS.append([p, {"channel_dim": 1}, (1, 3, 4, 2)])
     TESTS.append([p, {"channel_dim": 3}, (1, 2, 3, 4)])
+    TESTS.append([p, {"channel_dim": (1, 2)}, (1, 4, 2, 3)])
 
 
 class TestAsChannelLast(unittest.TestCase):
diff --git a/tests/test_as_channel_lastd.py b/tests/test_as_channel_lastd.py
index a6d94d216a..35ca9208ed 100644
--- a/tests/test_as_channel_lastd.py
+++ b/tests/test_as_channel_lastd.py
@@ -22,6 +22,7 @@
     TESTS.append([p, {"keys": ["image", "label", "extra"], "channel_dim": 0}, (2, 3, 4, 1)])
     TESTS.append([p, {"keys": ["image", "label", "extra"], "channel_dim": 1}, (1, 3, 4, 2)])
     TESTS.append([p, {"keys": ["image", "label", "extra"], "channel_dim": 3}, (1, 2, 3, 4)])
+    TESTS.append([p, {"keys": ["image", "label", "extra"], "channel_dim": (1, 0)}, (3, 4, 2, 1)])
 
 
 class TestAsChannelLastd(unittest.TestCase):