Core elements in pydicom

pydicom object model, description of classes, examples

Dataset

dataset.Dataset is the main object you will work with directly. Dataset wraps a dictionary, where the key is the DICOM (group,element) tag (as a Tag object, described below), and the value is a DataElement instance (also described below). It implements most of the methods of dict, so that it mostly behaves like the wrapped dict. This allows direct access to the data elements via the the tags, as shown below.

Note

The iterator of a DataSet yields DataElement values, e.g. the values of the dictionary, as opposed to the keys yielded by a dict iterator.

A dataset could be created directly, but you will usually get one by reading an existing DICOM file:

>>> import pydicom
>>> from pydicom.data import get_testdata_files
>>> # get some test data
>>> filename = get_testdata_files("rtplan.dcm")[0]
>>> ds = pydicom.dcmread(filename)

You can display the entire dataset by simply printing its string (str or repr) value:

>>> ds 
(0008, 0012) Instance Creation Date              DA: '20030903'
(0008, 0013) Instance Creation Time              TM: '150031'
(0008, 0016) SOP Class UID                       UI: RT Plan Storage
(0008, 0018) SOP Instance UID                    UI: 1.2.777.777.77.7.7777.7777.20030903150023
(0008, 0020) Study Date                          DA: '20030716'
(0008, 0030) Study Time                          TM: '153557'
(0008, 0050) Accession Number                    SH: ''
(0008, 0060) Modality                            CS: 'RTPLAN'
...

Note

You can also view DICOM files in a collapsible tree using the example program dcm_qt_tree.py.

You can access specific data elements by name (DICOM ‘keyword’) or by DICOM tag number:

>>> ds.PatientName
'Last^First^mid^pre'
>>> ds[0x10,0x10].value
'Last^First^mid^pre'

In the latter case (using the tag number directly) a DataElement instance is returned, so the .value must be used to get the value.

Note

In pydicom, private data elements are displayed with square brackets around the name (if the name is known to pydicom). These are shown for convenience only; the descriptive name in brackets cannot be used to retrieve data elements. See details in Private Data Elements.

You can also set values by name (DICOM keyword) or tag number:

>>> ds.PatientID = "12345"
>>> ds.SeriesNumber = 5
>>> ds[0x10,0x10].value = 'Test'

The use of names is possible because pydicom intercepts requests for member variables, and checks if they are in the DICOM dictionary. It translates the keyword to a (group,element) number and returns the corresponding value for that key if it exists.

See Anonymize DICOM data for a usage example of data elements removal and assignation.

Note

To understand using sequence.Sequences in pydicom, please refer to this object model: dataset.Dataset (wraps a Python dict)

—> contains DataElement instances

–> the value of the data element can be one of:

  • a regular value like a number, string, etc.

  • a list of regular values (e.g. a 3-D coordinate)

  • a Sequence instance

–> a Sequence is a list of dataset.Dataset (and so we come full circle)

DICOM sequence.Sequences are turned into Python list s. Items in the sequence are referenced by number, beginning at index 0 as per Python convention:

>>> ds.BeamSequence[0].BeamName
'Field 1'
>>> # Or, set an intermediate variable to a dataset in the list
>>> beam1 = ds.BeamSequence[0]  # First dataset in the sequence
>>> beam1.BeamName
'Field 1'

See Working with sequences.

Using DICOM keywords is the recommended way to access data elements, but you can also use the tag numbers directly, such as:

>>> # Same thing with tag numbers - much harder to read:
>>> # Really should only be used if DICOM keyword not in pydicom dictionary
>>> ds[0x300a,0xb0][0][0x300a,0xc2].value
'Field 1'

If you don’t remember or know the exact tag name (aka DICOM keyword), dataset.Dataset provides a handy dataset.Dataset.dir() method, useful during interactive sessions at the Python prompt:

>>> ds.dir("pat")
['PatientBirthDate', 'PatientID', 'PatientName', 'PatientSetupSequence', 'PatientSex']

dataset.Dataset.dir() will return any DICOM tag names in the dataset that have the specified string anywhere in the name (case insensitive).

Note

Calling dataset.Dataset.dir() with no string will list all tag names available in the dataset.

You can also see all the names that pydicom knows about by viewing the _dicom_dict.py file. It should not normally be necessary, but you can add your own entries to the DICOM dictionary at run time using datadict.add_dict_entries() or datadict.add_dict_entry(). Similarly, you can add private data elements to the private dictionary using datadict.add_private_dict_entries() or datadict.add_private_dict_entries().

Under the hood, dataset.Dataset stores a DataElement object for each item, but when accessed by name (e.g. ds.PatientName) only the value of that dataelem.DataElement is returned. If you need the whole dataelem (see the dataelem.DataElement discussion), you can use the dataset.Dataset.data_element() method or access the item using the tag number:

>>> # reload the data
>>> ds = pydicom.dcmread(filename)
>>> data_element = ds.data_element("PatientName")
>>> data_element.VR, data_element.value
('PN', 'Last^First^mid^pre')
>>> # an alternative is to use:
>>> data_element = ds[0x10,0x10]
>>> data_element.VR, data_element.value
('PN', 'Last^First^mid^pre')

To check for the existence of a particular tag before using it, use the in keyword:

>>> "PatientName" in ds
True

To remove a data element from the dataset, use python’s del statement:

>>> del ds.SoftwareVersions   # or del ds[0x0018, 0x1020]

To work with pixel data, the raw bytes are available through the usual tag:

>>> # read data with actual pixel data
>>> filename = get_testdata_files("CT_small.dcm")[0]
>>> ds = pydicom.dcmread(filename)
>>> pixel_bytes = ds.PixelData

but to work with them in a more intelligent way, use Dataset.pixel_array() (requires the NumPy library):

>>> pix = ds.pixel_array
>>> pix 
array([[175, 180, 166, ..., 203, 207, 216],
       [186, 183, 157, ..., 181, 190, 239],
       [184, 180, 171, ..., 152, 164, 235],
       ...,
       [906, 910, 923, ..., 922, 929, 927],
       [914, 954, 938, ..., 942, 925, 905],
       [959, 955, 916, ..., 911, 904, 909]], dtype=int16)

For more details, see Working with Pixel Data.

DataElement

The dataelem.DataElement class is not usually used directly in user code, but is used extensively by dataset.Dataset. dataelem.DataElement is a simple object which stores the following things:

  • tag – a DICOM tag (as a Tag object)

  • VR – DICOM value representation – various number and string formats, etc

  • VM – value multiplicity. This is 1 for most DICOM tags, but can be multiple, e.g. for coordinates. You do not have to specify this, the DataElement class keeps track of it based on value.

  • value – the actual value. A regular value like a number or string (or list of them), or a Sequence.

Tag

Tag is not generally used directly in user code, as Tags are automatically created when you assign or read data elements using the DICOM keywords as illustrated in sections above.

The Tag class is derived from Python’s int, so in effect, it is just a number with some extra behaviour:

  • Tag enforces that the DICOM tag fits in the expected 4-byte (group,element)

  • A Tag instance can be created from an int or a tuple containing the (group,element), or from the DICOM keyword:

    >>> from pydicom.tag import Tag
    >>> t1 = Tag(0x00100010) # all of these are equivalent
    >>> t2 = Tag(0x10,0x10)
    >>> t3 = Tag((0x10, 0x10))
    >>> t4 = Tag("PatientName")
    >>> t1
    (0010, 0010)
    >>> t1==t2, t1==t3, t1==t4
    (True, True, True)
    
  • Tag has properties group and element (or elem) to return the group and element portions

  • The is_private property checks whether the tag represents a private tag (i.e. if group number is odd).

Sequence

Sequence is derived from Python’s list. The only added functionality is to make string representations prettier. Otherwise all the usual methods of list like item selection, append, etc. are available.

For examples of accessing data nested in sequences, see Working with sequences.