6627 reading dcm folder filtering filenames

monai/apps/datasets.py

@@ -22,6 +22,7 @@
 import numpy as np
 
 from monai.apps.tcia import (
+    DCM_FILENAME_REGEX,
     download_tcia_series_instance,
     get_tcia_metadata,
     get_tcia_ref_uid,
@@ -442,6 +443,10 @@ class TciaDataset(Randomizable, CacheDataset):
         specific_tags: tags that will be loaded for "SEG" series. This argument will be used in
             `monai.data.PydicomReader`. Default is [(0x0008, 0x1115), (0x0008,0x1140), (0x3006, 0x0010),
             (0x0020,0x000D), (0x0010,0x0010), (0x0010,0x0020), (0x0020,0x0011), (0x0020,0x0012)].
+        fname_regex: a regular expression to match the file names when the input is a folder.
+            If provided, only the matched files will be included. For example, to include the file name
+            "image_0001.dcm", the regular expression could be `".*image_(\\d+).dcm"`.
+            Default to `"^(?!.*LICENSE).*"`, ignoring any file name containing `"LICENSE"`.
         val_frac: percentage of validation fraction in the whole dataset, default is 0.2.
         seed: random seed to randomly shuffle the datalist before splitting into training and validation, default is 0.
             note to set same seed for `training` and `validation` sections.
@@ -509,6 +514,7 @@ def __init__(
             (0x0020, 0x0011),  # Series Number
             (0x0020, 0x0012),  # Acquisition Number
         ),
+        fname_regex: str = DCM_FILENAME_REGEX,
         seed: int = 0,
         val_frac: float = 0.2,
         cache_num: int = sys.maxsize,
@@ -548,12 +554,13 @@ def __init__(
 
         if not os.path.exists(download_dir):
             raise RuntimeError(f"Cannot find dataset directory: {download_dir}.")
+        self.fname_regex = fname_regex
 
         self.indices: np.ndarray = np.array([])
         self.datalist = self._generate_data_list(download_dir)
 
         if transform == ():
-            transform = LoadImaged(reader="PydicomReader", keys=["image"])
+            transform = LoadImaged(keys=["image"], reader="PydicomReader", fname_regex=self.fname_regex)
         CacheDataset.__init__(
             self,
             data=self.datalist,

monai/apps/tcia/__init__.py

@@ -12,4 +12,11 @@
 from __future__ import annotations
 
 from .label_desc import TCIA_LABEL_DICT
-from .utils import download_tcia_series_instance, get_tcia_metadata, get_tcia_ref_uid, match_tcia_ref_uid_in_study
+from .utils import (
+    BASE_URL,
+    DCM_FILENAME_REGEX,
+    download_tcia_series_instance,
+    get_tcia_metadata,
+    get_tcia_ref_uid,
+    match_tcia_ref_uid_in_study,
+)

monai/apps/tcia/utils.py

@@ -21,10 +21,18 @@
 requests_get, has_requests = optional_import("requests", name="get")
 pd, has_pandas = optional_import("pandas")
 
-__all__ = ["get_tcia_metadata", "download_tcia_series_instance", "get_tcia_ref_uid", "match_tcia_ref_uid_in_study"]
-
+DCM_FILENAME_REGEX = r"^(?!.*LICENSE).*"  # excluding the file with "LICENSE" in its name
 BASE_URL = "https://services.cancerimagingarchive.net/nbia-api/services/v1/"
 
+__all__ = [
+    "get_tcia_metadata",
+    "download_tcia_series_instance",
+    "get_tcia_ref_uid",
+    "match_tcia_ref_uid_in_study",
+    "DCM_FILENAME_REGEX",
+    "BASE_URL",
+]
+
 
 def get_tcia_metadata(query: str, attribute: str | None = None) -> list:
     """

monai/data/image_reader.py

@@ -13,6 +13,7 @@
 
 import glob
 import os
+import re
 import warnings
 from abc import ABC, abstractmethod
 from collections.abc import Callable, Iterable, Iterator, Sequence
@@ -403,8 +404,12 @@ class PydicomReader(ImageReader):
         label_dict: label of the dicom data. If provided, it will be used when loading segmentation data.
             Keys of the dict are the classes, and values are the corresponding class number. For example:
             for TCIA collection "C4KC-KiTS", it can be: {"Kidney": 0, "Renal Tumor": 1}.
+        fname_regex: a regular expression to match the file names when the input is a folder.
+            If provided, only the matched files will be included. For example, to include the file name
+            "image_0001.dcm", the regular expression could be `".*image_(\\d+).dcm"`. Default to `""`.
+            Set it to `None` to use `pydicom.misc.is_dicom` to match valid files.
         kwargs: additional args for `pydicom.dcmread` API. more details about available args:
-            https://pydicom.github.io/pydicom/stable/reference/generated/pydicom.filereader.dcmread.html#pydicom.filereader.dcmread
+            https://pydicom.github.io/pydicom/stable/reference/generated/pydicom.filereader.dcmread.html
             If the `get_data` function will be called
             (for example, when using this reader with `monai.transforms.LoadImage`), please ensure that the argument
             `stop_before_pixels` is `True`, and `specific_tags` covers all necessary tags, such as `PixelSpacing`,
@@ -418,6 +423,7 @@ def __init__(
         swap_ij: bool = True,
         prune_metadata: bool = True,
         label_dict: dict | None = None,
+        fname_regex: str = "",
         **kwargs,
     ):
         super().__init__()
@@ -427,6 +433,7 @@ def __init__(
         self.swap_ij = swap_ij
         self.prune_metadata = prune_metadata
         self.label_dict = label_dict
+        self.fname_regex = fname_regex
 
     def verify_suffix(self, filename: Sequence[PathLike] | PathLike) -> bool:
         """
@@ -467,9 +474,16 @@ def read(self, data: Sequence[PathLike] | PathLike, **kwargs):
             name = f"{name}"
             if Path(name).is_dir():
                 # read DICOM series
-                series_slcs = glob.glob(os.path.join(name, "*"))
-                series_slcs = [slc for slc in series_slcs if "LICENSE" not in slc]
-                slices = [pydicom.dcmread(fp=slc, **kwargs_) for slc in series_slcs]
+                if self.fname_regex is not None:
+                    series_slcs = [slc for slc in glob.glob(os.path.join(name, "*")) if re.match(self.fname_regex, slc)]
+                else:
+                    series_slcs = [slc for slc in glob.glob(os.path.join(name, "*")) if pydicom.misc.is_dicom(slc)]
+                slices = []
+                for slc in series_slcs:
+                    try:
+                        slices.append(pydicom.dcmread(fp=slc, **kwargs_))
+                    except pydicom.errors.InvalidDicomError as e:
+                        warnings.warn(f"Failed to read {slc} with exception: \n{e}.", stacklevel=2)
                 img_.append(slices if len(slices) > 1 else slices[0])
                 if len(slices) > 1:
                     self.has_series = True

tests/test_load_image.py

@@ -226,6 +226,11 @@ def test_itk_dicom_series_reader(self, input_param, filenames, expected_shape, e
         )
         self.assertTupleEqual(result.shape, expected_np_shape)
 
+    def test_no_files(self):
+        with self.assertRaisesRegex(RuntimeError, "list index out of range"):  # fname_regex excludes everything
+            LoadImage(image_only=True, reader="PydicomReader", fname_regex=r"^(?!.*).*")("tests/testing_data/CT_DICOM")
+        LoadImage(image_only=True, reader="PydicomReader", fname_regex=None)("tests/testing_data/CT_DICOM")
+
     def test_itk_dicom_series_reader_single(self):
         result = LoadImage(image_only=True, reader="ITKReader")(self.data_dir)
         self.assertEqual(result.meta["filename_or_obj"], f"{Path(self.data_dir)}")

tests/test_tciadataset.py

@@ -16,7 +16,7 @@
 import unittest
 
 from monai.apps import TciaDataset
-from monai.apps.tcia import TCIA_LABEL_DICT
+from monai.apps.tcia import DCM_FILENAME_REGEX, TCIA_LABEL_DICT
 from monai.data import MetaTensor
 from monai.transforms import Compose, EnsureChannelFirstd, LoadImaged, ScaleIntensityd
 from tests.utils import skip_if_downloading_fails, skip_if_quick
@@ -32,7 +32,12 @@ def test_values(self):
 
         transform = Compose(
             [
-                LoadImaged(keys=["image", "seg"], reader="PydicomReader", label_dict=TCIA_LABEL_DICT[collection]),
+                LoadImaged(
+                    keys=["image", "seg"],
+                    reader="PydicomReader",
+                    fname_regex=DCM_FILENAME_REGEX,
+                    label_dict=TCIA_LABEL_DICT[collection],
+                ),
                 EnsureChannelFirstd(keys="image", channel_dim="no_channel"),
                 ScaleIntensityd(keys="image"),
             ]
@@ -82,10 +87,24 @@ def _test_dataset(dataset):
         self.assertTupleEqual(data[0]["image"].shape, (256, 256, 24))
         self.assertEqual(len(data), int(download_len * val_frac))
         data = TciaDataset(
-            root_dir=testing_dir, collection=collection, section="validation", download=False, val_frac=val_frac
+            root_dir=testing_dir,
+            collection=collection,
+            section="validation",
+            download=False,
+            fname_regex=DCM_FILENAME_REGEX,
+            val_frac=val_frac,
         )
         self.assertTupleEqual(data[0]["image"].shape, (256, 256, 24))
         self.assertEqual(len(data), download_len)
+        with self.assertWarns(UserWarning):
+            data = TciaDataset(
+                root_dir=testing_dir,
+                collection=collection,
+                section="validation",
+                fname_regex=".*",  # all files including 'LICENSE' is not a valid input
+                download=False,
+                val_frac=val_frac,
+            )[0]
 
         shutil.rmtree(os.path.join(testing_dir, collection))
         try: