4502-implement-pydicomreader

docs/requirements.txt

@@ -29,3 +29,4 @@ pyyaml
 fire
 jsonschema
 pynrrd
+pydicom

docs/source/installation.md

@@ -190,9 +190,9 @@ Since MONAI v0.2.0, the extras syntax such as `pip install 'monai[nibabel]'` is
 
 - The options are
 ```
-[nibabel, skimage, pillow, tensorboard, gdown, ignite, torchvision, itk, tqdm, lmdb, psutil, cucim, openslide, pandas, einops, transformers, mlflow, matplotlib, tensorboardX, tifffile, imagecodecs, pyyaml, fire, jsonschema, pynrrd]
+[nibabel, skimage, pillow, tensorboard, gdown, ignite, torchvision, itk, tqdm, lmdb, psutil, cucim, openslide, pandas, einops, transformers, mlflow, matplotlib, tensorboardX, tifffile, imagecodecs, pyyaml, fire, jsonschema, pynrrd, pydicom]
 ```
 which correspond to `nibabel`, `scikit-image`, `pillow`, `tensorboard`,
-`gdown`, `pytorch-ignite`, `torchvision`, `itk`, `tqdm`, `lmdb`, `psutil`, `cucim`, `openslide-python`, `pandas`, `einops`, `transformers`, `mlflow`, `matplotlib`, `tensorboardX`, `tifffile`, `imagecodecs`, `pyyaml`, `fire`, `jsonschema`, `pynrrd`, respectively.
+`gdown`, `pytorch-ignite`, `torchvision`, `itk`, `tqdm`, `lmdb`, `psutil`, `cucim`, `openslide-python`, `pandas`, `einops`, `transformers`, `mlflow`, `matplotlib`, `tensorboardX`, `tifffile`, `imagecodecs`, `pyyaml`, `fire`, `jsonschema`, `pynrrd`, `pydicom`, respectively.
 
 - `pip install 'monai[all]'` installs all the optional dependencies.

environment-dev.yml

@@ -46,6 +46,7 @@ dependencies:
   - fire
   - jsonschema
   - pynrrd
+  - pydicom
   - pip
   - pip:
     # pip for itk as conda-forge version only up to v5.1

monai/data/__init__.py

@@ -47,7 +47,7 @@
 from .folder_layout import FolderLayout
 from .grid_dataset import GridPatchDataset, PatchDataset, PatchIter, PatchIterd
 from .image_dataset import ImageDataset
-from .image_reader import ImageReader, ITKReader, NibabelReader, NrrdReader, NumpyReader, PILReader
+from .image_reader import ImageReader, ITKReader, NibabelReader, NrrdReader, NumpyReader, PILReader, PydicomReader
 from .image_writer import (
     SUPPORTED_WRITERS,
     ImageWriter,

monai/transforms/io/array.py

@@ -28,7 +28,15 @@
 from monai.config import DtypeLike, NdarrayOrTensor, PathLike
 from monai.data import image_writer
 from monai.data.folder_layout import FolderLayout
-from monai.data.image_reader import ImageReader, ITKReader, NibabelReader, NrrdReader, NumpyReader, PILReader
+from monai.data.image_reader import (
+    ImageReader,
+    ITKReader,
+    NibabelReader,
+    NrrdReader,
+    NumpyReader,
+    PILReader,
+    PydicomReader,
+)
 from monai.transforms.transform import Transform
 from monai.transforms.utility.array import EnsureChannelFirst
 from monai.utils import GridSampleMode, GridSamplePadMode
@@ -42,6 +50,7 @@
 __all__ = ["LoadImage", "SaveImage", "SUPPORTED_READERS"]
 
 SUPPORTED_READERS = {
+    "pydicomreader": PydicomReader,
     "itkreader": ITKReader,
     "nrrdreader": NrrdReader,
     "numpyreader": NumpyReader,
@@ -110,7 +119,7 @@ def __init__(
                 - if `reader` is None, a default set of `SUPPORTED_READERS` will be used.
                 - if `reader` is a string, it's treated as a class name or dotted path
                 (such as ``"monai.data.ITKReader"``), the supported built-in reader classes are
-                ``"ITKReader"``, ``"NibabelReader"``, ``"NumpyReader"``.
+                ``"ITKReader"``, ``"NibabelReader"``, ``"NumpyReader"``, ``"PydicomReader"``.
                 a reader instance will be constructed with the `*args` and `**kwargs` parameters.
                 - if `reader` is a reader class/instance, it will be registered to this loader accordingly.
             image_only: if True return only the image volume, otherwise return image data array and header dict.

requirements-dev.txt

@@ -49,3 +49,4 @@ fire
 jsonschema
 pynrrd
 pre-commit
+pydicom

setup.cfg

@@ -54,6 +54,7 @@ all =
     fire
     jsonschema
     pynrrd
+    pydicom
 nibabel =
     nibabel
 skimage =
@@ -104,6 +105,8 @@ jsonschema =
     jsonschema
 pynrrd =
     pynrrd
+pydicom =
+    pydicom
 
 [flake8]
 select = B,C,E,F,N,P,T4,W,B9

tests/test_init_reader.py

@@ -11,7 +11,7 @@
 
 import unittest
 
-from monai.data import ITKReader, NibabelReader, NrrdReader, NumpyReader, PILReader
+from monai.data import ITKReader, NibabelReader, NrrdReader, NumpyReader, PILReader, PydicomReader
 from monai.transforms import LoadImage, LoadImaged
 from tests.utils import SkipIfNoModule
 
@@ -23,14 +23,15 @@ def test_load_image(self):
         self.assertIsInstance(instance1, LoadImage)
         self.assertIsInstance(instance2, LoadImage)
 
-        for r in ["NibabelReader", "PILReader", "ITKReader", "NumpyReader", "NrrdReader", None]:
+        for r in ["NibabelReader", "PILReader", "ITKReader", "NumpyReader", "NrrdReader", "PydicomReader", None]:
             inst = LoadImaged("image", reader=r)
             self.assertIsInstance(inst, LoadImaged)
 
     @SkipIfNoModule("itk")
     @SkipIfNoModule("nibabel")
     @SkipIfNoModule("PIL")
     @SkipIfNoModule("nrrd")
+    @SkipIfNoModule("Pydicom")
     def test_readers(self):
         inst = ITKReader()
         self.assertIsInstance(inst, ITKReader)
@@ -40,6 +41,9 @@ def test_readers(self):
         inst = NibabelReader(as_closest_canonical=True)
         self.assertIsInstance(inst, NibabelReader)
 
+        inst = PydicomReader()
+        self.assertIsInstance(inst, PydicomReader)
+
         inst = NumpyReader()
         self.assertIsInstance(inst, NumpyReader)
         inst = NumpyReader(npz_keys="test")

tests/test_load_image.py

@@ -20,7 +20,7 @@
 from parameterized import parameterized
 from PIL import Image
 
-from monai.data import ITKReader, NibabelReader
+from monai.data import ITKReader, NibabelReader, PydicomReader
 from monai.transforms import LoadImage
 
 
@@ -134,6 +134,31 @@ def get_data(self, _obj):
     (128, 128, 3, 128),
 ]
 
+# test same dicom data with PydicomReader
+TEST_CASE_19 = [
+    {"image_only": False, "reader": PydicomReader()},
+    "tests/testing_data/CT_DICOM",
+    (16, 16, 4),
+    (16, 16, 4),
+]
+
+TEST_CASE_20 = [
+    {"image_only": False, "reader": "PydicomReader", "ensure_channel_first": True},
+    "tests/testing_data/CT_DICOM",
+    (16, 16, 4),
+    (1, 16, 16, 4),
+]
+
+TEST_CASE_21 = [
+    {"image_only": False, "reader": "PydicomReader", "affine_lps_to_ras": True, "defer_size": "2 MB"},
+    "tests/testing_data/CT_DICOM",
+    (16, 16, 4),
+    (16, 16, 4),
+]
+
+# test reader consistency between PydicomReader and ITKReader on dicom data
+TEST_CASE_22 = ["tests/testing_data/CT_DICOM"]
+
 
 class TestLoadImage(unittest.TestCase):
     @parameterized.expand(
@@ -174,7 +199,7 @@ def test_itk_reader(self, input_param, filenames, expected_shape):
                 np.testing.assert_allclose(header["original_affine"], np_diag)
             self.assertTupleEqual(result.shape, expected_shape)
 
-    @parameterized.expand([TEST_CASE_10, TEST_CASE_11, TEST_CASE_12])
+    @parameterized.expand([TEST_CASE_10, TEST_CASE_11, TEST_CASE_12, TEST_CASE_19, TEST_CASE_20, TEST_CASE_21])
     def test_itk_dicom_series_reader(self, input_param, filenames, expected_shape, expected_np_shape):
         result, header = LoadImage(**input_param)(filenames)
         self.assertTrue("affine" in header)
@@ -208,6 +233,18 @@ def test_itk_reader_multichannel(self):
                 np.testing.assert_allclose(result[:, :, 1], test_image[:, :, 1])
                 np.testing.assert_allclose(result[:, :, 2], test_image[:, :, 2])
 
+    @parameterized.expand([TEST_CASE_22])
+    def test_dicom_reader_consistency(self, filenames):
+        itk_param = {"reader": "ITKReader"}
+        pydicom_param = {"reader": "PydicomReader"}
+        for affine_flag in [True, False]:
+            itk_param["affine_lps_to_ras"] = affine_flag
+            pydicom_param["affine_lps_to_ras"] = affine_flag
+            itk_result, itk_header = LoadImage(**itk_param)(filenames)
+            pydicom_result, pydicom_header = LoadImage(**pydicom_param)(filenames)
+            np.testing.assert_allclose(pydicom_result, itk_result)
+            np.testing.assert_allclose(itk_header["affine"], pydicom_header["affine"])
+
     def test_load_nifti_multichannel(self):
         test_image = np.random.randint(0, 256, size=(31, 64, 16, 2)).astype(np.float32)
         with tempfile.TemporaryDirectory() as tempdir: