WIP: Volumetric Segmentations

docs/package.rst

@@ -75,6 +75,15 @@ highdicom.utils module
    :undoc-members:
    :show-inheritance:
 
+highdicom.volume module
++++++++++++++++++++++++
+
+.. automodule:: highdicom.volume
+   :members:
+   :inherited-members: pydicom.dataset.Dataset,pydicom.sequence.Sequence,Dataset,Sequence,list,str,DataElementSequence,enum.Enum,Enum,
+   :special-members: __call__
+   :undoc-members:
+   :show-inheritance:
 
 .. _highdicom-legacy-subpackage:
 

docs/seg.rst

@@ -447,7 +447,7 @@ segments. Note that passing a "label map" is purely a convenience provided by
 (`highdicom` splits the label map into multiple single-segment frames and
 stores these, as required by the standard).
 
-Therefore, The following snippet produces an equivalent SEG image to the
+Therefore, the following snippet produces an equivalent SEG image to the
 previous snippet, but passes the mask as a label map rather than as a stack of
 segments.
 

pyproject.toml

@@ -35,6 +35,7 @@ dependencies = [
     "pillow>=8.3",
     "pydicom>=3.0.1",
     "pyjpegls>=1.0.0",
+    "typing-extensions>=4.0.0",
 ]
 
 [project.optional-dependencies]

src/highdicom/__init__.py

@@ -34,11 +34,13 @@
     VOILUTTransformation,
 )
 from highdicom.enum import (
+    AxisHandedness,
     AnatomicalOrientationTypeValues,
     CoordinateSystemNames,
     ContentQualificationValues,
     DimensionOrganizationTypeValues,
     LateralityValues,
+    PadModes,
     PatientSexValues,
     PhotometricInterpretationValues,
     PixelRepresentationValues,
@@ -56,13 +58,16 @@
 from highdicom.uid import UID
 from highdicom import utils
 from highdicom.version import __version__
+from highdicom import volume
+
 
 __all__ = [
     'LUT',
     'UID',
     'VOILUT',
     'AlgorithmIdentificationSequence',
     'AnatomicalOrientationTypeValues',
+    'AxisHandedness',
     'ContentCreatorIdentificationCodeSequence',
     'ContentQualificationValues',
     'CoordinateSystemNames',
@@ -71,6 +76,7 @@
     'LateralityValues',
     'ModalityLUT',
     'ModalityLUTTransformation',
+    'PadModes',
     'PaletteColorLUT',
     'PaletteColorLUTTransformation',
     'PatientOrientationValuesBiped',
@@ -112,4 +118,5 @@
     'spatial',
     'sr',
     'utils',
+    'volume',
 ]

src/highdicom/_module_utils.py

@@ -216,7 +216,11 @@ def get_module_usage(
     return None
 
 
-def is_attribute_in_iod(attribute: str, sop_class_uid: str) -> bool:
+def is_attribute_in_iod(
+    attribute: str,
+    sop_class_uid: str,
+    exclude_path_elements: Sequence[str] | None = None,
+) -> bool:
     """Check whether an attribute is present within an IOD.
 
     Parameters
@@ -225,6 +229,9 @@ def is_attribute_in_iod(attribute: str, sop_class_uid: str) -> bool:
         Keyword for the attribute
     sop_class_uid: str
         SOP Class UID identifying the IOD.
+    exclude_path_elements: Sequence[str] | None, optional
+        If any of these elements are found anywhere in the attribute's path,
+        that occurrence is excluded.
 
     Returns
     -------
@@ -247,6 +254,11 @@ def is_attribute_in_iod(attribute: str, sop_class_uid: str) -> bool:
     for module in IOD_MODULE_MAP[iod_name]:
         module_attributes = MODULE_ATTRIBUTE_MAP[module['key']]
         for attr in module_attributes:
+            if exclude_path_elements is not None:
+                if any(
+                    p in exclude_path_elements for p in attr['path']
+                ):
+                    continue
             if attr['keyword'] == attribute:
                 return True
 
@@ -279,12 +291,17 @@ def does_iod_have_pixel_data(sop_class_uid: str) -> bool:
         'DoubleFloatPixelData',
     ]
     return any(
-        is_attribute_in_iod(attr, sop_class_uid) for attr in pixel_attrs
+        is_attribute_in_iod(
+            attr,
+            sop_class_uid,
+            exclude_path_elements=['IconImageSequence'],
+        ) for attr in pixel_attrs
     )
 
 
 def is_multiframe_image(dataset: Dataset):
     """Determine whether an image is a multiframe image.
+
     The definition used is whether the IOD allows for multiple frames, not
     whether this particular instance has more than one frame.
 

src/highdicom/ann/content.py

@@ -1,6 +1,7 @@
 """Content that is specific to Annotation IODs."""
 from copy import deepcopy
 from typing import cast, List, Optional, Sequence, Tuple, Union
+from typing_extensions import Self
 
 import numpy as np
 from pydicom.dataset import Dataset
@@ -119,7 +120,7 @@ def from_dataset(
         cls,
         dataset: Dataset,
         copy: bool = True
-    ) -> 'Measurements':
+    ) -> Self:
         """Construct instance from an existing dataset.
 
         Parameters
@@ -165,7 +166,7 @@ def from_dataset(
             )
         ]
 
-        return cast(Measurements, measurements)
+        return cast(cls, measurements)
 
 
 class AnnotationGroup(Dataset):
@@ -770,7 +771,7 @@ def from_dataset(
         cls,
         dataset: Dataset,
         copy: bool = True,
-    ) -> 'AnnotationGroup':
+    ) -> Self:
         """Construct instance from an existing dataset.
 
         Parameters
@@ -838,4 +839,4 @@ def from_dataset(
                 for ds in group.PrimaryAnatomicStructureSequence
             ]
 
-        return cast(AnnotationGroup, group)
+        return cast(cls, group)

src/highdicom/ann/sop.py

@@ -14,6 +14,7 @@
     Tuple,
     Union,
 )
+from typing_extensions import Self
 
 import numpy as np
 from pydicom import dcmread
@@ -418,7 +419,7 @@ def from_dataset(
         cls,
         dataset: Dataset,
         copy: bool = True,
-    ) -> 'MicroscopyBulkSimpleAnnotations':
+    ) -> Self:
         """Construct instance from an existing dataset.
 
         Parameters
@@ -450,14 +451,14 @@ def from_dataset(
             ann = deepcopy(dataset)
         else:
             ann = dataset
-        ann.__class__ = MicroscopyBulkSimpleAnnotations
+        ann.__class__ = cls
 
         ann.AnnotationGroupSequence = [
             AnnotationGroup.from_dataset(item, copy=copy)
             for item in ann.AnnotationGroupSequence
         ]
 
-        return cast(MicroscopyBulkSimpleAnnotations, ann)
+        return cast(cls, ann)
 
 
 def annread(