6985 metatensor_to_itk_image compatible space

monai/data/image_reader.py

@@ -1316,6 +1316,8 @@ def get_data(self, img: NrrdImage | list[NrrdImage]) -> tuple[np.ndarray, dict]:
 
             if self.affine_lps_to_ras:
                 header = self._switch_lps_ras(header)
+            if header.get(MetaKeys.SPACE, "left-posterior-superior") == "left-posterior-superior":
+                header[MetaKeys.SPACE] = SpaceKeys.LPS  # assuming LPS if not specified
 
             header[MetaKeys.AFFINE] = header[MetaKeys.ORIGINAL_AFFINE].copy()
             header[MetaKeys.SPATIAL_SHAPE] = header["sizes"]

monai/data/itk_torch_bridge.py

@@ -19,8 +19,9 @@
 from monai.config.type_definitions import DtypeLike
 from monai.data import ITKReader, ITKWriter
 from monai.data.meta_tensor import MetaTensor
+from monai.data.utils import orientation_ras_lps
 from monai.transforms import EnsureChannelFirst
-from monai.utils import convert_to_dst_type, optional_import
+from monai.utils import MetaKeys, SpaceKeys, convert_to_dst_type, optional_import
 
 if TYPE_CHECKING:
     import itk
@@ -83,12 +84,18 @@ def metatensor_to_itk_image(
 
     See also: :py:func:`ITKWriter.create_backend_obj`
     """
+    if meta_tensor.meta.get(MetaKeys.SPACE, SpaceKeys.LPS) == SpaceKeys.RAS:
+        _meta_tensor = meta_tensor.clone()
+        _meta_tensor.affine = orientation_ras_lps(meta_tensor.affine)
+        _meta_tensor.meta[MetaKeys.SPACE] = SpaceKeys.LPS
+    else:
+        _meta_tensor = meta_tensor
     writer = ITKWriter(output_dtype=dtype, affine_lps_to_ras=False)
     writer.set_data_array(data_array=meta_tensor.data, channel_dim=channel_dim, squeeze_end_dims=True)
     return writer.create_backend_obj(
         writer.data_obj,
         channel_dim=writer.channel_dim,
-        affine=meta_tensor.affine,
+        affine=_meta_tensor.affine,
         affine_lps_to_ras=False,  # False if the affine is in itk convention
         dtype=writer.output_dtype,
         kwargs=kwargs,

tests/test_itk_torch_bridge.py

@@ -11,13 +11,17 @@
 
 from __future__ import annotations
 
+import itertools
 import os
+import tempfile
 import unittest
 
 import numpy as np
 import torch
 from parameterized import parameterized
 
+import monai
+import monai.transforms as mt
 from monai.apps import download_url
 from monai.data import ITKReader
 from monai.data.itk_torch_bridge import (
@@ -31,14 +35,17 @@
 from monai.networks.blocks import Warp
 from monai.transforms import Affine
 from monai.utils import optional_import, set_determinism
-from tests.utils import skip_if_downloading_fails, skip_if_quick, test_is_quick, testing_data_config
+from tests.utils import assert_allclose, skip_if_downloading_fails, skip_if_quick, test_is_quick, testing_data_config
 
 itk, has_itk = optional_import("itk")
+_, has_nib = optional_import("nibabel")
 
 TESTS = ["CT_2D_head_fixed.mha", "CT_2D_head_moving.mha"]
 if not test_is_quick():
     TESTS += ["copd1_highres_INSP_STD_COPD_img.nii.gz", "copd1_highres_EXP_STD_COPD_img.nii.gz"]
 
+RW_TESTS = TESTS + ["nrrd_example.nrrd"]
+
 
 @unittest.skipUnless(has_itk, "Requires `itk` package.")
 class TestITKTorchAffineMatrixBridge(unittest.TestCase):
@@ -47,7 +54,7 @@ def setUp(self):
         self.data_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "testing_data")
         self.reader = ITKReader(pixel_type=itk.F)
 
-        for file_name in TESTS:
+        for file_name in RW_TESTS:
             path = os.path.join(self.data_dir, file_name)
             if not os.path.exists(path):
                 with skip_if_downloading_fails():
@@ -482,5 +489,34 @@ def test_use_reference_space(self, ref_filepath, filepath):
         np.testing.assert_allclose(output_array_monai, output_array_itk, rtol=1e-3, atol=1e-3)
 
 
+@unittest.skipUnless(has_itk, "Requires `itk` package.")
+@unittest.skipUnless(has_nib, "Requires `nibabel` package.")
+@skip_if_quick
+class TestITKTorchRW(unittest.TestCase):
+    def setUp(self):
+        TestITKTorchAffineMatrixBridge.setUp(self)
+
+    def tearDown(self):
+        TestITKTorchAffineMatrixBridge.setUp(self)
+
+    @parameterized.expand(list(itertools.product(RW_TESTS, ["ITKReader", "NrrdReader"], [True, False])))
+    def test_rw_itk(self, filepath, reader, flip):
+        """reading and convert: filepath, reader, flip"""
+        print(filepath, reader, flip)
+        fname = os.path.join(self.data_dir, filepath)
+        xform = mt.LoadImageD("img", image_only=True, ensure_channel_first=True, affine_lps_to_ras=flip, reader=reader)
+        out = xform({"img": fname})["img"]
+        itk_image = metatensor_to_itk_image(out, channel_dim=0, dtype=float)
+        with tempfile.TemporaryDirectory() as tempdir:
+            tname = os.path.join(tempdir, filepath) + (".nii.gz" if not filepath.endswith(".nii.gz") else "")
+            itk.imwrite(itk_image, tname, True)
+            ref = mt.LoadImage(image_only=True, ensure_channel_first=True, reader="NibabelReader")(tname)
+        if out.meta["space"] != ref.meta["space"]:
+            ref.affine = monai.data.utils.orientation_ras_lps(ref.affine)
+        assert_allclose(
+            out.affine, monai.data.utils.to_affine_nd(len(out.affine) - 1, ref.affine), rtol=1e-3, atol=1e-3
+        )
+
+
 if __name__ == "__main__":
     unittest.main()

tests/testing_data/data_config.json

@@ -84,6 +84,11 @@
             "url": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/CT_DICOM_SINGLE.zip",
             "hash_type": "sha256",
             "hash_val": "a41f6e93d2e3d68956144f9a847273041d36441da12377d6a1d5ae610e0a7023"
+        },
+        "nrrd_example": {
+            "url": "https://github.com/Project-MONAI/MONAI-extra-test-data/releases/download/0.8.1/CT_IMAGE_cropped.nrrd",
+            "hash_type": "sha256",
+            "hash_val": "66971ad17f0bac50e6082ed6a4dc1ae7093c30517137e53327b15a752327a1c0"
         }
     },
     "videos": {