Fix #8442: simplify channel-first call and add regression test

Apply review suggestion: pass meta_data unconditionally to
EnsureChannelFirst — when img is a MetaTensor, EnsureChannelFirst
overrides meta_dict with img.meta internally, so the explicit if/else
is not needed.

Add regression test covering set_track_meta(False) with
ensure_channel_first=True on LoadImage.

Signed-off-by: UGBOMEH OGOCHUKWU WILLIAMS <williamsugbomeh@gmail.com>

Author: williams145

monai/transforms/io/array.py

@@ -300,10 +300,7 @@ def __call__(self, filename: Sequence[PathLike] | PathLike, reader: ImageReader
             img_array, meta_data, self.simple_keys, pattern=self.pattern, sep=self.sep
         )
         if self.ensure_channel_first:
-            if not isinstance(img, MetaTensor):
-                img = EnsureChannelFirst()(img, meta_dict=meta_data)
-            else:
-                img = EnsureChannelFirst()(img)
+            img = EnsureChannelFirst()(img, meta_dict=meta_data)
         if self.image_only:
             return img
         return img, img.meta if isinstance(img, MetaTensor) else meta_data

tests/transforms/test_load_image.py

@@ -497,6 +497,16 @@ def test_correct(self, input_param, expected_shape, track_meta):
             self.assertNotIsInstance(r, MetaTensor)
             self.assertFalse(hasattr(r, "affine"))
 
+    def test_track_meta_false_ensure_channel_first(self):
+        try:
+            set_track_meta(False)
+            r = LoadImage(image_only=True, ensure_channel_first=True)(self.test_data)
+            self.assertTupleEqual(r.shape, (1, 128, 128, 128))
+            self.assertIsInstance(r, torch.Tensor)
+            self.assertNotIsInstance(r, MetaTensor)
+        finally:
+            set_track_meta(True)
+
 
 if __name__ == "__main__":
     unittest.main()