ImagingDataCommons · CPBridge · Feb 12, 2026 · Feb 11, 2026 · Feb 11, 2026 · Feb 11, 2026
diff --git a/docs/coding.rst b/docs/coding.rst
@@ -79,7 +79,7 @@ value in `pydicom`:
 
    tumor_code = codes.SCT.Tumor
    print(tumor_code.value)
-   # '1083690006'
+   # '108369006'
    print(tumor_code.scheme_designator)
    # 'SCT'
    print(tumor_code.meaning)

diff --git a/docs/development.rst b/docs/development.rst
@@ -23,7 +23,7 @@ Pull requests
 
 We encourage contributions from the users of the library (provided that they fit within the scope of the project).
 
-If you are planning to make a contribution to the library, we encourage you to leave an issue first on the `issue tracker <https://github.com/ImagingDataCommons/higdicom/issues>`_ detailing your proposed contribution.
+If you are planning to make a contribution to the library, we encourage you to leave an issue first on the `issue tracker <https://github.com/ImagingDataCommons/highdicom/issues>`_ detailing your proposed contribution.
 This way, the maintainers can vet your proposal, make sure it is within the scope of the project, and guide you through the process of creating a successful pull request.
 Before creating a pull request on Github, read the coding style guideline, run the tests and check PEP8 compliance.
 

diff --git a/docs/generalsr.rst b/docs/generalsr.rst
@@ -9,10 +9,10 @@ supports structured reports through the :mod:`highdicom.sr` sub-package.
 
 SRs are highly complex, and this page attempts to give a basic introduction
 while also describing the implementation within `highdicom`. A more thorough
-explanation my be found in:
+explanation may be found in:
 
 * *DICOM Structured Reporting*. David Clunie. PixelMed Publishing, 2000.
-  Digital copy available 
+  Digital copy available
   `here <https://www.dclunie.com/pixelmed/DICOMSR.book.pdf>`_.
 
 Content Items
@@ -53,7 +53,7 @@ item. The classes representing these content items in `highdicom` are:
 - :class:`highdicom.sr.UIDRefContentItem`: The value is a UID (unique
   identifier).
 
-These classes are all subclasses pf ``pydicom.Dataset`` and you can view and
+These classes are all subclasses of ``pydicom.Dataset`` and you can view and
 interact with their attributes as you can with any pydicom dataset.
 
 You can look at the API for each class to see how to construct content items of

diff --git a/docs/image.rst b/docs/image.rst
@@ -72,7 +72,7 @@ frames of the image:
   (see :doc:`pixel_transforms` for more details on pixel transforms), but by
   default any pixel transform found in the dataset except the value-of-interest
   (VOI) transform is applied. This should be your default way of accessing
-  image frames in most cases, since it will typtically return the pixels as the
+  image frames in most cases, since it will typically return the pixels as the
   creator of the object intended them to be understood. By default, the
   returned frames have datatype ``numpy.float64``, but this can be controlled
   using the ``dtype`` parameter.

diff --git a/docs/release_notes.rst b/docs/release_notes.rst
@@ -113,13 +113,13 @@ systems, which are shifted by 0.5 pixels.
 1. **Pixel indices**: (column, row) indices into the pixel matrix. The values
    are zero-based integers in the range [0, Columns - 1] and [0, Rows - 1].
    Pixel indices are defined relative to the centers of pixels and the (0, 0)
-   index is located at the center of the top left corner hand pixel of the
+   index is located at the center of the top left corner pixel of the
    total pixel matrix.
 2. **Image coordinates**: (column, row) coordinates in the pixel matrix at
    sub-pixel resolution. The values are floating-point numbers in the range
    [0, Columns] and [0, Rows]. Image coordinates are defined relative to the
    top left corner of the pixels and the (0.0, 0.0) point is located at the top
-   left corner of the top left corner hand pixel of the total pixel matrix.
+   left corner of the top left corner pixel of the total pixel matrix.
 
 To account for these differences, introduced two additional transformer classes
 in highdicom 0.14.1. and made changes to the existing ones.

diff --git a/docs/remote.rst b/docs/remote.rst
@@ -59,7 +59,7 @@ spatial patch from a large whole slide image from the IDC.
   with blob.open(mode="rb", chunk_size=500_000) as reader:
       im = hd.imread(reader, lazy_frame_retrieval=True)
 
-      # Grab an arbitrary region of tile full pixel matrix
+      # Grab an arbitrary region of the full pixel matrix
       region = im.get_total_pixel_matrix(
           row_start=15000,
           row_end=15512,
@@ -163,11 +163,11 @@ the ``s3fs`` documentation for details).
   # URL to a whole slide image from the IDC "CCDS MCI" collection on AWS S3
   url = 's3://idc-open-data/763fe058-7d25-4ba7-9b29-fd3d6c41dc4b/210f0529-c767-4795-9acf-bad2f4877427.dcm'
 
-  # Read the imge directly from the blob
+  # Read the image directly from the blob
   with s3_client.open(url, mode="rb") as reader:
       im = hd.imread(reader, lazy_frame_retrieval=True)
 
-      # Grab an arbitrary region of tile full pixel matrix
+      # Grab an arbitrary region of the full pixel matrix
       region = im.get_total_pixel_matrix(
           row_start=15000,
           row_end=15512,

diff --git a/docs/seg.rst b/docs/seg.rst
@@ -53,7 +53,7 @@ are numbered with consecutive segment numbers starting at 1 (i.e., 1, 2, 3,
 ...).  Additionally, each segment present is accompanied by information
 describing what the segment represents. This information is placed in the
 "SegmentsSequence" (0062, 0002) attribute of the segmentation file. In
-*highdcom*, we use the :class:`highdicom.seg.SegmentDescription` class to hold
+*highdicom*, we use the :class:`highdicom.seg.SegmentDescription` class to hold
 this information. This is not to be confused with the DICOM "Segment
 Description" attribute, which is a plain text string. When you construct a
 DICOM SEG image using *highdicom*, you must construct a single

diff --git a/docs/tid1500.rst b/docs/tid1500.rst
@@ -4,7 +4,7 @@ The TID1500 Measurement Report Template
 =======================================
 
 The `TID1500 "Measurement Report" <tid1500def_>`_ template is a general-purpose
-template for communicating measurements and qualitative qualitative evaluations
+template for communicating measurements and qualitative evaluations
 derived from one or more images or regions of images. It is recommended to read
 the previous page on :ref:`generalsr` before this page.
 
@@ -460,7 +460,7 @@ type (some have been omitted for brevity):
 - ``measurements``: (Sequence of :class:`highdicom.sr.Measurement`, optional)
     Numeric measurements
 - ``qualitative_evaluations``: (Sequence of :class:`highdicom.sr.CodedConcept`, optional)
-    Coded name-value pairs that describe qualitative qualitative_evaluations
+    Coded name-value pairs that describe qualitative evaluations
 - ``finding_category``: (:class:`highdicom.sr.CodedConcept`, optional)
     Category of observed finding, e.g., anatomic structure or
     morphologically abnormal structure
@@ -482,7 +482,7 @@ Qualitative Evaluations
 A Qualitative Evaluation is essentially a categorical value inferred from an
 image. For example, this could represent a diagnosis derived from the
 referenced region or a severity grading. These are represented in *highdicom*
-using the class :class:`highdicom.sr.QualitativeEvalution`, which is
+using the class :class:`highdicom.sr.QualitativeEvaluation`, which is
 essentially a single :class:`highdicom.sr.CodeContentItem` within a special
 template.
 
@@ -495,15 +495,15 @@ parameters as coded values:
     from pydicom.sr.codedict import codes
 
     # An evaluation of disease severity as "mild"
-    severity_item = hd.sr.QualitativeEvalution(
+    severity_item = hd.sr.QualitativeEvaluation(
        name=codes.SCT.Severity,
        value=codes.SCT.Mild,
     )
 
     # An evaluation of tumor morphology as adenocarcinoma
-    morphology_item = hd.sr.QualitativeEvalution(
+    morphology_item = hd.sr.QualitativeEvaluation(
        name=codes.SCT.AssociatedMorphology,
-       value=codes.SCT.Anenocarcinoma,
+       value=codes.SCT.Adenocarcinoma,
     )
 
 Measurements (`TID300 <tid300def_>`_)

diff --git a/docs/tid1500parsing.rst b/docs/tid1500parsing.rst
@@ -233,7 +233,7 @@ A volumetric group returns a :class:`highdicom.sr.VolumeSurface` or list of
 :class:`highdicom.sr.ImageRegion` objects, depending on the reference type. If
 instead, a planar/volumetric measurement group uses the ``ReferencedSegment``
 reference type, the referenced segment can be accessed by the
-``group.referenced_segmention_frame`` property (for planar groups) or
+``group.referenced_segmentation_frame`` property (for planar groups) or
 ``group.referenced_segment`` property (for volumetric groups), which return
 objects of type :class:`highdicom.sr.ReferencedSegmentationFrame` and
 :class:`highdicom.sr.ReferencedSegment` respectively.

diff --git a/docs/volume.rst b/docs/volume.rst
@@ -81,7 +81,7 @@ to "LPS" convention for you.
 
 The top-left 3x3 matrix of the affine matrix consists of three orthogonal
 column vectors that give the vector travelled when incrementing the voxel
-indices in each o the three dimensions. The top three elements of the last
+indices in each of the three dimensions. The top three elements of the last
 column give the position of the voxel at index ``(0, 0, 0)``. The bottom row is
 always ``[0., 0., 0., 1.]``. The :meth:`highdicom.Volume.from_components()`
 method allows you to construct a volume by specifying these components of the

diff --git a/examples/README.md b/examples/README.md
@@ -11,4 +11,4 @@ docker build . -t highdicom/examples:latest
 docker run --rm --name highdicom_examples -p 8888:8888 highdicom/examples:latest
 ```
 
-After running the above commands, following the instructions printed into the standard output stream to access the notebooks in your browser.
+After running the above commands, follow the instructions printed into the standard output stream to access the notebooks in your browser.