Remove pinning highest versions of monai.

monai/deploy/operators/dicom_series_to_volume_operator.py

@@ -39,6 +39,11 @@ class DICOMSeriesToVolumeOperator(Operator):
         image: Image object.
     """
 
+    # Use constants instead of enums in monai to avoid dependency at this level.
+    MONAI_UTIL_ENUMS_SPACEKEYS_LPS = "LPS"
+    MONAI_TRANSFORMS_SPATIAL_METADATA_NAME = "space"
+    METADATA_SPACE_LPS = {MONAI_TRANSFORMS_SPATIAL_METADATA_NAME: MONAI_UTIL_ENUMS_SPACEKEYS_LPS}
+
     def __init__(self, fragment: Fragment, *args, **kwargs):
         """Create an instance for a containing application object.
 
@@ -84,6 +89,18 @@ def convert_to_image(self, study_selected_series_list: List[StudySelectedSeries]
             metadata.update(self._get_instance_properties(study_selected_series.study))
             selection_metadata = {"selection_name": selection_name}
             metadata.update(selection_metadata)
+            # Add the metadata to specify LPS.
+            # Previously, this was set in ImageReader class, but moving it here allows other loaders
+            # to determine this value on its own, e.g. NIfTI loader but it does not set this
+            # resulting in the MONAI Orientation transform to default the labels to RAS.
+            # It is assumed that the ImageOrientationPatient will be set accordingly if the
+            # PatientPosition is other than HFS.
+            # NOTE: This value is properly parsed by MONAI Orientation transform from v1.5.1 onwards.
+            #       Some early MONAI model inference configs incorrectly specify orientation to RAS
+            #       due part to previous MONAI versions did not correctly parse this metadata from
+            #       the input MetaTensor and defaulting to RAS. Now with LPS properly set, the inference
+            #       configs then need to be updated to specify LPS, to achieve the same result.
+            metadata.update(self.METADATA_SPACE_LPS)
 
             voxel_data = self.generate_voxel_data(dicom_series)
             image = self.create_volumetric_image(voxel_data, metadata)

monai/deploy/operators/monai_bundle_inference_operator.py

@@ -614,7 +614,7 @@ def _init_config(self, config_names):
         )
 
     def _get_compose(self, obj_name, disallowed_prefixes):
-        """Gets a Compose object containing a sequence fo transforms from item `obj_name` in `self._parser`."""
+        """Gets a Compose object containing a sequence of transforms from item `obj_name` in `self._parser`."""
 
         if self._parser.get(obj_name) is not None:
             compose = self._parser.get_parsed_content(obj_name)
@@ -749,6 +749,7 @@ def compute(self, op_input, op_output, context):
                     raise ValueError("`meta_data` must be a dict.")
                 value = MetaTensor.ensure_torch_and_prune_meta(value, meta_data)
                 inputs[name] = value
+                logging.debug(f"Input MetaTensor metadata 'space': {value.meta.get('space', None)}")
                 # Named metadata dict not needed any more, as it is in the MetaTensor
 
             inputs = self.pre_process(inputs)
@@ -1062,7 +1063,8 @@ def _convert_from_image_dicom_source(self, img: Image) -> Tuple[np.ndarray, Dict
         # Use defines MetaKeys directly
         meta_dict[MetaKeys.ORIGINAL_AFFINE] = np.asarray(img_meta_dict.get("nifti_affine_transform", None))
         meta_dict[MetaKeys.AFFINE] = meta_dict[MetaKeys.ORIGINAL_AFFINE].copy()
-        meta_dict[MetaKeys.SPACE] = SpaceKeys.LPS  # not using SpaceKeys.RAS or affine_lps_to_ras
+        # Disabled setting the SPACE key below as it has changed to be set in the actual loader implementation.
+        # meta_dict[MetaKeys.SPACE] = SpaceKeys.LPS  # not using SpaceKeys.RAS or affine_lps_to_ras
 
         # Similarly the Image ndarray has dim order DHW, to be rearranged to WHD.
         # TODO: Need to revisit this once multi-channel image is supported and the Image class itself

monai/deploy/operators/monai_seg_inference_operator.py

@@ -90,7 +90,7 @@ def filter_sw_kwargs(**kwargs) -> Tuple[Dict[str, Any], Dict[str, Any]]:
             - Are not explicitly defined in the __init__ of this class
             - Are not explicitly used when calling sliding_window_inference
 
-        2. A dicionary of named parameters to pass to the base class __init__ of this class that:
+        2. A dictionary of named parameters to pass to the base class __init__ of this class that:
             - Are not used when calling sliding_window_inference
             - Can be successfully converted from Python --> Holoscan's C++ layer
 
@@ -582,7 +582,8 @@ def _get_meta_dict(self, img: Image) -> Dict:
         # Use define metadata kyes directly
         meta_dict[MetaKeys.ORIGINAL_AFFINE] = np.asarray(img_meta_dict.get("nifti_affine_transform", None))
         meta_dict[MetaKeys.AFFINE] = meta_dict[MetaKeys.ORIGINAL_AFFINE].copy()
-        meta_dict[MetaKeys.SPACE] = SpaceKeys.LPS  # not using SpaceKeys.RAS or affine_lps_to_ras
+        # Disabled setting the SPACE key below as it has changed to be set in the actual loader implementation.
+        # meta_dict[MetaKeys.SPACE] = SpaceKeys.LPS  # not using SpaceKeys.RAS or affine_lps_to_ras
         # The spatial shape, again, referring to ITKReader, it is the WHD
         meta_dict[MetaKeys.SPATIAL_SHAPE] = np.asarray(img.asnumpy().T.shape)
         # Well, no channel as the image data shape is forced to the the same as spatial shape