A DICOM dataset as a mutable mapping of DICOM Data Elements.
Examples
Add an element to the Dataset (for elements in the DICOM dictionary):
>>> ds = Dataset() >>> ds.PatientName = "CITIZEN^Joan" >>> ds.add_new(0x00100020, 'LO', '12345') >>> ds[0x0010, 0x0030] = DataElement(0x00100030, 'DA', '20010101')
Add a sequence element to the Dataset
>>> ds.BeamSequence = [Dataset(), Dataset(), Dataset()] >>> ds.BeamSequence[0].Manufacturer = "Linac, co." >>> ds.BeamSequence[1].Manufacturer = "Linac and Sons, co." >>> ds.BeamSequence[2].Manufacturer = "Linac and Daughters, co."
Add private elements to the Dataset
>>> block = ds.private_block(0x0041, 'My Creator', create=True) >>> block.add_new(0x01, 'LO', '12345')
Updating and retrieving element values:
>>> ds.PatientName = "CITIZEN^Joan" >>> ds.PatientName 'CITIZEN^Joan' >>> ds.PatientName = "CITIZEN^John" >>> ds.PatientName 'CITIZEN^John'
Retrieving an element’s value from a Sequence:
>>> ds.BeamSequence[0].Manufacturer 'Linac, co.' >>> ds.BeamSequence[1].Manufacturer 'Linac and Sons, co.'
Accessing the DataElement items:
>>> elem = ds['PatientName']
>>> elem
(0010,0010) Patient's Name PN: 'CITIZEN^John'
>>> elem = ds[0x00100010]
>>> elem
(0010,0010) Patient's Name PN: 'CITIZEN^John'
>>> elem = ds.data_element('PatientName')
>>> elem
(0010,0010) Patient's Name PN: 'CITIZEN^John'
Accessing a private DataElement item:
>>> block = ds.private_block(0x0041, 'My Creator') >>> elem = block[0x01] >>> elem (0041,1001) Private tag data LO: '12345' >>> elem.value '12345'
Alternatively:
>>> ds.get_private_item(0x0041, 0x01, 'My Creator').value '12345'
Deleting an element from the Dataset
>>> del ds.PatientID >>> del ds.BeamSequence[1].Manufacturer >>> del ds.BeamSequence[2]
Deleting a private element from the Dataset
>>> block = ds.private_block(0x0041, 'My Creator') >>> if 0x01 in block: ... del block[0x01]
Determining if an element is present in the Dataset
>>> 'PatientName' in ds True >>> 'PatientID' in ds False >>> (0x0010, 0x0030) in ds True >>> 'Manufacturer' in ds.BeamSequence[0] True
Iterating through the top level of a Dataset only (excluding Sequences):
>>> for elem in ds: ... print(elem) (0010,0010) Patient's Name PN: 'CITIZEN^John'
Iterating through the entire Dataset (including Sequences):
>>> for elem in ds.iterall(): ... print(elem) (0010,0010) Patient's Name PN: 'CITIZEN^John'
Recursively iterate through a Dataset (including Sequences):
>>> def recurse(ds): ... for elem in ds: ... if elem.VR == 'SQ': ... [recurse(item) for item in elem.value] ... else: ... # Do something useful with each DataElement
Converting the Dataset to and from JSON:
>>> ds = Dataset() >>> ds.PatientName = "Some^Name" >>> jsonmodel = ds.to_json() >>> ds2 = Dataset() >>> ds2.from_json(jsonmodel) (0010,0010) Patient's Name PN: 'Some^Name'
The default formatting for string display.
The default formatting for string display of sequences.
For string display, the characters used to indent nested Sequences. Default is " ".
Create a new Dataset instance.
Methods
Attributes
Add an element to the Dataset.
Equivalent to ds[data_element.tag] = data_element
data_element (dataelem.DataElement) – The DataElement to add.
Create a new element and add it to the Dataset.
tag – The DICOM (group, element) tag in any form accepted by Tag() such as [0x0010, 0x0010], (0x10, 0x10), 0x00100010, etc.
VR (str) – The 2 character DICOM value representation (see DICOM Standard, Part 5, Section 6.2).
value –
The value of the data element. One of the following:
Create a new private element and add it to the Dataset.
private_creator (str) – The private creator string related to the new tag.
group (int) – The group ID (0x0009 - 0xFFFF) for the private tag. Must be an odd number.
element_offset (int) – The tag offset, e.g. the lower byte of the tag element of the private tag (0x00 - 0xFF). The higher byte is defined by the location of the private creator tag.
value (Any) –
The value of the data element. One of the following:
vr (str | None) – The two-letter DICOM value representation, or None. If set to None, it is taken from the private tag dictionary.
ValueError – If group doesn’t belong to a private tag or private_creator is empty.
KeyError – If vr is None and the tag is not found in the private tag dictionary.
Delete all the elements from the Dataset.
Compress uncompressed pixel data and update ds in-place with the resulting encapsulated codestream.
Added in version 2.2.
The dataset ds must already have the following Image Pixel module elements present with correct values that correspond to the resulting compressed pixel data:
(0028,0002) Samples per Pixel
(0028,0004) Photometric Interpretation
(0028,0008) Number of Frames (if more than 1 frame will be present)
(0028,0010) Rows
(0028,0011) Columns
(0028,0100) Bits Allocated
(0028,0101) Bits Stored
(0028,0103) Pixel Representation
If Samples per Pixel is greater than 1 then the following element is also required:
(0028,0006) Planar Configuration
This method will add the file meta dataset if none is present and add or modify the following elements:
(0002,0010) Transfer Syntax UID
(7FE0,0010) Pixel Data
If the compressed pixel data is too large for encapsulation using a basic offset table then an extended offset table will also be used, in which case the following elements will also be added:
(7FE0,0001) Extended Offset Table
(7FE0,0002) Extended Offset Table Lengths
If performing lossy compression then a new (0008,0018) SOP Instance UID value will be generated unless generate_instance_uid is False.
Supported Transfer Syntax UIDs
Changed in version 3.0: Added the jls_error, j2k_cr, j2k_psnr and generate_instance_uid keyword parameters.
Changed in version 3.1: Added support for Deflated Image Frame Compression
Examples
Compress the existing uncompressed Pixel Data in place:
>>> from pydicom import examples
>>> from pydicom.uid import RLELossless
>>> ds = examples.ct
>>> ds.compress(RLELossless)
>>> ds.save_as("ct_rle_lossless.dcm")
transfer_syntax_uid (pydicom.uid.UID) – The UID of the transfer syntax to use when compressing the pixel data.
arr (numpy.ndarray, optional) – Compress the uncompressed pixel data in arr and use it to set the Pixel Data. If arr is not used then the existing Pixel Data in the dataset will be compressed instead. The shape, dtype and contents of the array should match the dataset.
encoding_plugin (str, optional) – Use the encoding_plugin to compress the pixel data. See the user guide for a list of plugins available for each UID and their dependencies. If not specified then all available plugins will be tried (default).
encapsulate_ext (bool, optional) – If True then force the addition of an extended offset table. If False (default) then an extended offset table will be added if needed for large amounts of compressed Pixel Data, otherwise just the basic offset table will be used.
generate_instance_uid (bool, optional) – If True then always generate a new (0008,0018) SOP Instance UID using generate_uid(), otherwise False to always keep the original. The default behavior is to only generate a new SOP Instance UID when performing lossy compression.
jls_error (int, optional) – JPEG-LS Near Lossless only. The allowed absolute compression error in the pixel values.
j2k_cr (list[float], optional) – JPEG 2000 only. A list of the compression ratios to use for each quality layer. There must be at least one quality layer and the minimum allowable compression ratio is 1. When using multiple quality layers they should be ordered in decreasing value from left to right. For example, to use 2 quality layers with 20x and 5x compression ratios then j2k_cr should be [20, 5]. Cannot be used with j2k_psnr.
j2k_psnr (list[float], optional) – JPEG 2000 only. A list of the peak signal-to-noise ratios (in dB) to use for each quality layer. There must be at least one quality layer and when using multiple quality layers they should be ordered in increasing value from left to right. For example, to use 2 quality layers with PSNR of 80 and 300 then j2k_psnr should be [80, 300]. Cannot be used with j2k_cr.
**kwargs – Optional keyword parameters for the encoding plugin may also be present. See the encoding plugins options for more information.
Convert pixel data to a numpy.ndarray internally.
Deprecated since version 3.0: This method will be removed in v4.0, use pixel_array_options() instead.
handler_name (str, optional) –
The name of the pixel handler or decoding plugin to use to decode the dataset’s pixel data. Support values are:
If using the pixel_data_handlers backend: 'gdcm', 'pillow', 'jpeg_ls', 'rle', 'numpy' and 'pylibjpeg'.
If using the pixels backend see the documentation for the decoder corresponding to the dataset’s Transfer Syntax UID.
If not used (the default) then all available handlers or plugins will be tried and the data from first successful one will be used.
Converted pixel data is stored internally in the dataset, it can be accessed with the pixel_array property.
None
ValueError – If handler_name is not a valid handler name.
NotImplementedError – If the given handler or any handler, if none given, is unable to decompress pixel data with the current transfer syntax
RuntimeError – If the given handler, or the handler that has been selected if none given, is not available.
Notes
If the pixel data is in a compressed image format, the data is decompressed and any related data elements are changed accordingly.
Return a shallow copy of the dataset.
Return the element corresponding to the element keyword name.
name (str) – A DICOM element keyword.
For the given DICOM element keyword, return the corresponding DataElement if present, None otherwise.
dataelem.DataElement or None
Apply character set decoding to the elements in the Dataset.
See DICOM Standard, Part 5, Section 6.1.1.
Perform an in-place decompression of a dataset with a compressed Transfer Syntax UID.
The dataset’s Transfer Syntax UID will be set to Explicit VR Little Endian.
The Pixel Data will be decompressed in its entirety and the Pixel Data element’s value updated with the decompressed data, padded to an even length.
The Pixel Data element’s VR will be set to OB if Bits Allocated <= 8, otherwise it will be set to OW.
The DataElement.is_undefined_length attribute for the Pixel Data element will be set to False.
Any image pixel module elements may be modified as required to match the uncompressed Pixel Data.
If the color space has been converted from YCbCr to RGB then a new (0008,0018) SOP Instance UID value will be generated unless generate_instance_uid is False.
Changed in version 3.0: Added the as_rgb and generate_instance_uid keyword parameters.
Deprecated since version 3.0: The handler_name parameter will be removed in v4.0, use decoding_plugin instead.
handler_name (str, optional) – Deprecated and will be removed in v4.0, use decoding_plugin instead.
as_rgb (bool, optional) – pixels backend only. If True (default) then convert pixel data with a YCbCr photometric interpretation such as "YBR_FULL_422" to RGB.
generate_instance_uid (bool, optional) – If True then always generate a new (0008,0018) SOP Instance UID, using generate_uid(), otherwise False to always keep the original. The default behavior is to only generate a new SOP Instance UID when the image data has had a YCbCr to RGB conversion applied.
decoding_plugin (str, optional) –
The name of the decoding plugin to use when decoding compressed pixel data. If no decoding_plugin is specified (default) then all available plugins will be tried and the result from the first successful one yielded.
If using the pixels backend (default) then see the API documentation for the available plugins for each Transfer Syntax UID.
If using the deprecated pixel_data_handlers backend supported plugins are: 'gdcm', 'pillow', 'jpeg_ls', 'rle', 'numpy' and 'pylibjpeg'.
kwargs (dict[str, Any], optional) – pixels backend only. Optional keyword parameters for the decoding plugin may also be present. See the decoding plugins options for more information.
Return an alphabetical list of element keywords in the Dataset.
Intended mainly for use in interactive Python sessions. Only lists the element keywords in the current level of the Dataset (i.e. the contents of any sequence elements are ignored).
Yield the top-level elements of the Dataset.
Examples
>>> ds = Dataset() >>> for elem in ds.elements(): ... print(elem)
The elements are returned in the same way as in Dataset.__getitem__().
dataelem.DataElement or dataelem.RawDataElement – The unconverted elements sorted by increasing tag order.
Create an empty Dataset.file_meta if none exists.
Iterate through the Dataset yielding formatted str for each element.
element_format (str) – The string format to use for non-sequence elements. Formatting uses the attributes of DataElement. Default is "%(tag)s %(name)-35.35s %(VR)s: %(repval)s".
sequence_element_format (str) – The string format to use for sequence elements. Formatting uses the attributes of DataElement. Default is "%(tag)s %(name)-35.35s %(VR)s: %(repval)s"
indent_format (str or None) – Placeholder for future functionality.
str – A string representation of an element.
Return a Dataset from a DICOM JSON Model object.
See the DICOM Standard, Part 18, Annex F.
json_dataset (dict, str, bytes or bytearray) – dict, str, bytes or bytearray representing a DICOM Data Set formatted based on the DICOM JSON Model.
bulk_data_uri_handler (callable, optional) – Callable function that accepts either the tag, vr and “BulkDataURI” value or just the “BulkDataURI” value of the JSON representation of a data element and returns the actual value of that data element (retrieved via DICOMweb WADO-RS). If no bulk_data_uri_handler is specified (default) then the corresponding element will have an “empty” value such as "", b"" or None depending on the vr (i.e. the Value Multiplicity will be 0).
Simulate dict.get() to handle element tags and keywords.
value – If key is the keyword for an element in the Dataset then return the element’s value.
dataelem.DataElement – If key is a tag for a element in the Dataset then return the DataElement instance.
value – If key is a class attribute then return its value.
Return the raw data element if possible.
It will be raw if the user has never accessed the value, or set their own value. Note if the data element is a deferred-read element, then it is read and converted before being returned.
key – The DICOM (group, element) tag in any form accepted by Tag() such as [0x0010, 0x0010], (0x10, 0x10), 0x00100010, etc. May also be a slice made up of DICOM tags.
keep_deferred (bool, optional) – If True then when returning RawDataElement do not perform the deferred read of the element’s value (accessing the value will return None instead). Default False.
The corresponding element.
Return the data element for the given private tag group.
This is analogous to Dataset.__getitem__(), but only for private tags. This allows to find the private tag for the correct private creator without the need to add the tag to the private dictionary first.
The corresponding element.
ValueError – If group is not part of a private tag or private_creator is empty.
KeyError – If the private creator tag is not found in the given group. If the private tag is not found.
Return a Dataset containing only elements of a certain group.
Return True if the dataset uses an uncompressed (native) transfer syntax, False otherwise.
Added in version 3.1.
Get/set the VR method used when encoding the dataset.
Deprecated since version 3.0: is_implicit_VR will be removed in v4.0, set the Transfer Syntax UID or use the implicit_vr argument with save_as() or dcmwrite() instead.
If the dataset has been created from scratch then returns None, otherwise returns the VR encoding method used by the decoded dataset.
bool | None
Get/set the endianness used when encoding the dataset.
Deprecated since version 3.0: is_little_endian will be removed in v4.0, set the Transfer Syntax UID or use the little_endian argument with save_as() or dcmwrite() instead.
If the dataset has been created from scratch then returns None, otherwise returns the endianness of the encoding used by the decoded dataset.
bool | None
Return True if the encoding to be used for writing is set and is the same as that used to originally encode the Dataset.
This includes properties related to endianness, VR handling and the (0008,0005) Specific Character Set.
Return the Dataset items to simulate dict.items().
The top-level (BaseTag, DataElement) items for the Dataset.
dict_items
Iterate through the Dataset, yielding all the elements.
Unlike iter(Dataset), this does recurse into sequences, and so yields all elements as if dataset were “flattened”.
dataelem.DataElement
Return the Dataset keys to simulate dict.keys().
Return the original character set encoding for a dataset decoded from a file or buffer.
Return the original encoding used for a dataset decoded from a file or buffer.
Return the Overlay Data in group as a numpy.ndarray.
group (int) – The group number of the overlay data.
The (group,3000) Overlay Data converted to a numpy.ndarray.
Return the pixel data as a numpy.ndarray.
Changed in version 3.0: The backend used for pixel data decoding has changed from the pixel_data_handlers module to the pixels module. The behavior of the new backend is not backwards compatible with the old one, in particular the default color space should now be RGB when previously YCbCr data was returned.
To revert to the deprecated pixel_data_handlers backend pass use_v2_backend=True to the pixel_array_options() method:
>>> from pydicom import examples >>> ds = examples.ct >>> ds.pixel_array_options(use_v2_backend=True) >>> arr = ds.pixel_array
The pixel_data_handlers module and the use_v2_backend keyword argument will be removed in v4.0.
The contents of the (7FE0,0008) Float Pixel Data, (7FE0,0009) Double Float Pixel Data or (7FE0,0010) Pixel Data elements converted to a numpy.ndarray. The array will be shaped as:
(rows, columns) for single frame, single sample data
(rows, columns, samples) for single frame, multi-sample data
(frames, rows, columns) for multi-frame, single sample data
(frames, rows, columns, samples) for multi-frame, multi-sample data
When using the pydicom.pixels backend the decoding options used with the returned array can be customized via the pixel_array_options() method.
Set the decoding and processing options used by the pixel_array property.
Added in version 3.0.
Deprecated since version 3.0: The use_v2_backend keyword parameter will be removed in v4.0.
Processing
The following processing operations on the raw pixel data will always be performed:
Natively encoded bit-packed pixel data for a bits allocated of 1 will be unpacked.
Natively encoded pixel data with a photometric interpretation of "YBR_FULL_422" will have it’s sub-sampling removed.
The output array will be reshaped to the specified dimensions.
JPEG-LS or JPEG 2000 encoded data whose signedness doesn’t match the expected pixel representation will be converted to match.
With the pydicom.pixels backend, if raw = False (the default) then the following processing operation will also be performed:
Pixel data with a photometric interpretation of "YBR_FULL" or "YBR_FULL_422" will be converted to RGB.
Examples
Convert the Pixel Data to an array that’s a view on the original buffer:
>>> from pydicom import examples >>> ds = examples.ct >>> ds.pixel_array_options(view_only=True) >>> arr = ds.pixel_array
Use the deprecated pixel_data_handlers backend to convert the Pixel Data to an array:
>>> from pydicom import examples >>> ds = examples.ct >>> ds.pixel_array_options(use_v2_backend=True) >>> arr = ds.pixel_array
index (int | None, optional) – If None (default) then return an array containing all the frames in the pixel data, otherwise return one containing only the frame from the specified index, which starts at 0 for the first frame. Only available with the pixels backend.
raw (bool, optional) – If True then return the decoded pixel data after only minimal processing (see the processing section above). If False (default) then additional processing may be applied to convert the pixel data to it’s most commonly used form (such as converting from YCbCr to RGB). Only available with the pixels backend.
decoding_plugin (str, optional) –
The name of the decoding plugin to use when decoding compressed pixel data. If no decoding_plugin is specified (default) then all available plugins will be tried and the result from the first successful one returned. For information on the available plugins for each Transfer Syntax UID:
If using the pixels backend see the documentation for the decoder corresponding to the dataset’s Transfer Syntax UID.
If using the pixel_data_handlers backend supported values are 'gdcm', 'pillow', 'jpeg_ls', 'rle', 'numpy' and 'pylibjpeg'.
use_v2_backend (bool, optional) – If False (default) then use the pydicom.pixels backend to decode the pixel data, otherwise use the deprecated pydicom.pixel_data_handlers backend.
**kwargs – Optional keyword parameters for controlling decoding with the pixels backend, please see the decoding options documentation for more information.
Emulate dict.pop() with support for tags and keywords.
Removes the element for key if it exists and returns it, otherwise returns a default value if given or raises KeyError.
*args (zero or one argument) – Defines the behavior if no tag exists for key: if given, it defines the return value, if not given, KeyError is raised
The element for key if it exists, or the default value if given.
KeyError – If the key is not a valid tag or keyword. If the tag does not exist and no default is given.
Emulate dict.popitem().
tuple of (BaseTag, DataElement)
Return the block for the given tag group and private_creator.
If create is True and the private_creator does not exist, the private creator tag is added.
Notes
We ignore the unrealistic case that no free block is available.
group (int) – The group of the private tag to be found as a 32-bit int. Must be an odd number (e.g. a private group).
private_creator (str) – The private creator string associated with the tag.
create (bool, optional) – If True and private_creator does not exist, a new private creator tag is added at the next free block. If False (the default) and private_creator does not exist, KeyError is raised instead.
The existing or newly created private block.
ValueError – If group doesn’t belong to a private tag or private_creator is empty.
KeyError – If the private creator tag is not found in the given group and the create parameter is False.
Return a list of private creator names in the given group.
Examples
This can be used to check if a given private creator exists in the group of the dataset:
>>> ds = Dataset() >>> if 'My Creator' in ds.private_creators(0x0041): ... block = ds.private_block(0x0041, 'My Creator')
group (int) – The private group as a 32-bit int. Must be an odd number.
All private creator names for private blocks in the group.
ValueError – If group is not a private group.
Return the original character set encoding for a decoded dataset.
Deprecated since version 3.0: read_encoding will be removed in v4.0, use original_character_set instead.
Get the VR method used by the original encoding of the dataset.
Deprecated since version 3.0: read_implicit_vr will be removed in v4.0, , use original_encoding instead.
Returns None if the dataset has been created from scratch, otherwise returns True if the dataset was decoded from file or buffer and used implicit VR, False if it used explicit VR.
bool | None
Get the endianness used by the original encoding of the dataset.
Deprecated since version 3.0: read_little_endian will be removed in v4.0, use original_encoding instead.
Returns None if the dataset has been created from scratch, otherwise returns True if the dataset was decoded from file or buffer and used little endian encoding, False for big endian.
bool | None
Remove all private elements from the Dataset.
Encode the current Dataset and write it to filename.
See the documentation for dcmwrite() for more detailed information.
Warning
Encoding a dataset with little_endian=False (i.e. as big endian) is not recommended. Big endian encoding was retired from the DICOM Standard in 2006.
Warning
This function cannot be used to convert a decoded dataset to an encoding that uses a different endianness, such as from big to little endian. dcmwrite() must be used instead, however the process is not automatic. See the documentation of dcmwrite() for details.
Changed in version 3.0: Added implicit_vr, little_endian, enforce_file_format and overwrite keyword arguments
Deprecated since version 3.0: write_like_original will be removed in v4.0, please use enforce_file_format instead
filename (str | PathLike | BinaryIO) – The path, file-like or writeable buffer to write the encoded dataset to. If using a buffer it must have write(), seek() and tell() methods.
write_like_original (bool, optional) – If True (default) then write the dataset as-is, otherwise ensure that the dataset is written in the DICOM File Format or raise an exception is that isn’t possible. This parameter is deprecated, please use enforce_file_format instead.
implicit_vr (bool, optional) – Required if the dataset has no valid public Transfer Syntax UID set in the file meta and is_implicit_VR or original_encoding are None. If True then encode using implicit VR, otherwise use explicit VR.
little_endian (bool, optional) – Required if the dataset has no valid public Transfer Syntax UID set in the file meta and is_little_endian or original_encoding are None. If True (default) then use little endian byte order when encoding, otherwise use big endian (not recommended).
enforce_file_format (bool, optional) –
If True then ensure the dataset is written in the DICOM File Format or raise an exception if that isn’t possible. If False (default) then write the dataset as-is, preserving the following - which may result in a non-conformant file:
Dataset.preamble: if the dataset has no preamble then none will be written
Dataset.file_meta: if the dataset is missing any required File Meta Information Group elements then they will not be added or written
overwrite (bool, optional) – If False and filename is a str or PathLike, then raise a FileExistsError if a file already exists with the given filename (default True).
Set the values for the original dataset encoding.
Can be used for a Dataset with raw data elements to enable optimized writing (e.g. without decoding the data elements).
Changed in version 3.0: character_encoding is now optional
is_implicit_vr (bool | None) – The the original VR encoding of the dataset, True for implicit VR, False for explicit VR or None to reset.
is_little_endian (bool | None) – Set the original endianness of the dataset, True for little endian, False for big or None to reset.
character_encoding (str | MutableSequence[str], optional) – Set the original character set encoding of the dataset. If None then no changes will be made to the original character set encoding.
Use an ndarray to set the Pixel Data and related Image Pixel module elements.
Added in version 3.0.
The following Image Pixel module elements values will be added, updated or removed as necessary:
(0028,0002) Samples per Pixel using a value corresponding to photometric_interpretation.
(0028,0104) Photometric Interpretation from photometric_interpretation.
(0028,0006) Planar Configuration will be added and set to 0 if Samples per Pixel is > 1, otherwise it will be removed.
(0028,0008) Number of Frames from the array shape, however it will be removed if arr only contains a single frame.
(0028,0010) Rows and (0028,0011) Columns from the array shape.
(0028,0100) Bits Allocated from the array dtype.
(0028,0101) Bits Stored and (0028,0102) High Bit from bits_stored.
(0028,0103) Pixel Representation from the array dtype.
In addition:
The Transfer Syntax UID will be set to Explicit VR Little Endian if it doesn’t already exist or uses a compressed (encapsulated) transfer syntax.
If generate_instance_uid is True (default) then the SOP Instance UID will be added or updated.
If a bool array is used then the pixel data will be bit-packed using pack_bits().
Changed in version 3.1: Added the ability to use a bool ndarray for Bits Allocated 1 with bit-packing.
arr (numpy.ndarray) –
An array with dtype bool, uint8, uint16, int8, or int16. The array must be shaped as one of the following:
(rows, columns) for a single frame of grayscale data.
(frames, rows, columns) for multi-frame grayscale data.
(rows, columns, samples) for a single frame of multi-sample data such as RGB.
(frames, rows, columns, samples) for multi-frame, multi-sample data.
photometric_interpretation (str) – The value to use for (0028,0004) Photometric Interpretation. Valid values are "MONOCHROME1", "MONOCHROME2", "PALETTE COLOR", "RGB", "YBR_FULL", "YBR_FULL_422".
bits_stored (int) – The value to use for (0028,0101) Bits Stored. Must be no greater than the number of bits used by the itemsize of arr, or 1 in the case of an array of dtype bool.
generate_instance_uid (bool, optional) – If True (default) then add or update the (0008,0018) SOP Instance UID element with a value generated using generate_uid().
NotImplementedError – If the dataset has a big-endian Transfer Syntax UID.
Emulate dict.setdefault() with support for tags and keywords.
Examples
>>> ds = Dataset()
>>> elem = ds.setdefault((0x0010, 0x0010), "Test")
>>> elem
(0010,0010) Patient's Name PN: 'Test'
>>> elem.value
'Test'
>>> elem = ds.setdefault('PatientSex',
... DataElement(0x00100040, 'CS', 'F'))
>>> elem.value
'F'
default (pydicom.dataelem.DataElement or object, optional) – The DataElement to use with key, or the value of the DataElement to use with key (default None).
The DataElement for key.
ValueError – If key is not convertible to a valid tag or a known element keyword.
KeyError – If reading_validation_mode is RAISE and key is an unknown non-private tag.
Return a JSON representation of the Dataset.
See the DICOM Standard, Part 18, Annex F.
bulk_data_threshold (int, optional) – Threshold for the length of a base64-encoded binary data element above which the element should be considered bulk data and the value provided as a URI rather than included inline (default: 1024). Ignored if no bulk data handler is given.
bulk_data_element_handler (callable, optional) – Callable function that accepts a bulk data element and returns a JSON representation of the data element (dictionary including the “vr” key and either the “InlineBinary” or the “BulkDataURI” key).
dump_handler (callable, optional) –
Callable function that accepts a dict and returns the serialized (dumped) JSON string (by default uses json.dumps()).
suppress_invalid_tags (bool, optional) – Flag to specify if errors while serializing tags should be logged and the tag dropped or if the error should be bubbled up.
Dataset serialized into a string based on the DICOM JSON Model.
Examples
>>> def my_json_dumps(data): ... return json.dumps(data, indent=4, sort_keys=True) >>> ds.to_json(dump_handler=my_json_dumps)
Return a dictionary representation of the Dataset conforming to the DICOM JSON Model as described in the DICOM Standard, Part 18, Annex F.
bulk_data_threshold (int, optional) – Threshold for the length of a base64-encoded binary data element above which the element should be considered bulk data and the value provided as a URI rather than included inline (default: 1024). Ignored if no bulk data handler is given.
bulk_data_element_handler (callable, optional) – Callable function that accepts a bulk data element and returns a JSON representation of the data element (dictionary including the “vr” key and either the “InlineBinary” or the “BulkDataURI” key).
suppress_invalid_tags (bool, optional) – Flag to specify if errors while serializing tags should be logged and the tag dropped or if the error should be bubbled up.
Dataset representation based on the DICOM JSON Model.
Return a str representation of the top level elements.
Return a list of valid names for auto-completion code.
Used in IPython, so that data element names can be found and offered for autocompletion on the IPython command line.
Extend dict.update() to handle DICOM tags and keywords.
Modify the VR or value for the raw element with tag.
When a Dataset is created most of it’s elements are in their RawDataElement form, and only upon trying to access the element is it converted to a DataElement. When this conversion fails due to non-conformance issues, this method can be used to modify the raw element data prior to conversion in order to fix any issues.
Example
Change the VR for the element with tag (0029,1026) before conversion to DataElement.
>>> from pydicom import examples >>> ds = examples.ct >>> ds.update_raw_element(0x00291026, vr="US") >>> elem = ds[0x00291026] # conversion to DataElement occurs here >>> type(elem) <class 'pydicom.dataelem.DataElement'> >>> elem.VR "US"
tag (int | str | tuple[int, int] | BaseTag) – The tag for a RawDataElement in the dataset.
vr (str, optional) – Required if value is not used, the value to use for the modified element’s VR, if not used then the existing VR will be kept.
value (bytes, optional) – Required if vr is not used, the value to use for the modified element’s raw encoded value, if not used then the existing value will be kept.
Return the Dataset values to simulate dict.values().
The DataElements that make up the values of the Dataset.
dict_keys
Iterate through the Dataset's elements and run callback on each.
Visit all elements in the Dataset, possibly recursing into sequences and their items. The callback function is called for each DataElement (including elements with a VR of ‘SQ’). Can be used to perform an operation on certain types of elements.
For example, remove_private_tags() finds all elements with private tags and deletes them.
The elements will be returned in order of increasing tag number within their current Dataset.
callback –
A callable function that takes two arguments:
a Dataset
a DataElement belonging to that Dataset
recursive (bool, optional) – Flag to indicate whether to recurse into sequences (default True).
Return an ndarray for the multiplex group at index in the (5400,0100) Waveform Sequence.
Added in version 2.1.
index (int) – The index of the multiplex group to return the array for.
The Waveform Data for the multiplex group as an ndarray with shape (samples, channels). If (003A,0210) Channel Sensitivity is present then the values will be in the units specified by the (003A,0211) Channel Sensitivity Units Sequence.
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