Fix issue within TraceableTransform

Previously, a method was defined in `meta_tensor`, and using `data_array.clone()` introduced additional costs.
After reevaluating the code, modifying the `TraceableTransform.track_transform_meta()` method executed by `SpatialResample` makes it much cleaner and more maintainable.

Signed-off-by: Wei_Chuan, Chiang <[email protected]>
Co-authored-by: einsyang723 <[email protected]>
Co-authored-by: IamTingTing  <[email protected]>

Author: 3 people

monai/data/meta_tensor.py

@@ -477,10 +477,6 @@ def pixdim(self):
             return [affine_to_spacing(a) for a in self.affine]
         return affine_to_spacing(self.affine)
 
-    def set_pixdim(self) -> None:
-        """Update pixdim based on current affine."""
-        self.meta[MetaKeys.PIXDIM][1 : 1 + len(self.pixdim)] = affine_to_spacing(self.affine)
-
     def peek_pending_shape(self):
         """
         Get the currently expected spatial shape as if all the pending operations are executed.

monai/transforms/inverse.py

@@ -21,7 +21,7 @@
 from monai import transforms
 from monai.data.meta_obj import MetaObj, get_track_meta
 from monai.data.meta_tensor import MetaTensor
-from monai.data.utils import to_affine_nd
+from monai.data.utils import to_affine_nd, affine_to_spacing
 from monai.transforms.traits import InvertibleTrait
 from monai.transforms.transform import Transform
 from monai.utils import (
@@ -197,6 +197,8 @@ def track_transform_meta(
                 else:
                     raise
             out_obj.meta[MetaKeys.AFFINE] = convert_to_tensor(affine, device=torch.device("cpu"), dtype=torch.float64)
+            out_obj.meta[MetaKeys.PIXDIM] = affine_to_spacing(out_obj.meta[MetaKeys.AFFINE])
+
 
         if not (get_track_meta() and transform_info and transform_info.get(TraceKeys.TRACING)):
             if isinstance(data, Mapping):

monai/transforms/spatial/array.py

@@ -535,9 +535,6 @@ def __call__(
             dtype=dtype,
             lazy=lazy_,
         )
-        if isinstance(data_array, MetaTensor) and "pixdim" in data_array.meta:
-            data_array = cast(MetaTensor, data_array.clone())
-            data_array.set_pixdim()
         if self.recompute_affine and isinstance(data_array, MetaTensor):
             if lazy_:
                 raise NotImplementedError("recompute_affine is not supported with lazy evaluation.")