Compressing Pixel Data

How to compress Pixel Data

Compressing using pydicom

Supported Transfer Syntaxes

Pixel Data can be compressed natively using pydicom for the following transfer syntaxes:

Transfer Syntax

Plugin names

Dependencies

Name

UID

JPEG-LS Lossless

1.2.840.10008.1.2.4.80

pyjpegls

numpy, pyjpegls

JPEG-LS Near Lossless

1.2.840.10008.1.2.4.81

JPEG 2000 Lossless

1.2.840.10008.1.2.4.90

pylibjpeg

numpy, pylibjpeg, pylibjpeg-openjpeg

JPEG 2000

1.2.840.10008.1.2.4.91

RLE Lossless

1.2.840.10008.1.2.5

pydicom 1

pylibjpeg

numpy, pylibjpeg, pylibjpeg-rle

gdcm

gdcm
1 ~20x slower than the other plugins

Each of the supported transfer syntaxes has a corresponding encoding guide to help you with the specific requirements of the encoding method.

Transfer Syntax

Encoding guide

JPEG-LS Lossless

JPEG-LS Encoding

JPEG-LS Near Lossless

JPEG 2000 Lossless

JPEG 2000 Encoding

JPEG 2000

RLE Lossless

RLE Encoding

Compressing with Dataset.compress()

The Dataset.compress() method or compress() function can be used to compress an uncompressed dataset in-place:

from pydicom import examples
from pydicom.uid import RLELossless

ds = examples.ct
ds.compress(RLELossless)
ds.save_as("ct_rle_lossless.dcm")

A specific encoding plugin can be used by passing the plugin name via the encoding_plugin argument:

# Will set `ds.is_little_endian` and `ds.is_implicit_VR` automatically
ds.compress(RLELossless, encoding_plugin='pylibjpeg')
ds.save_as("ct_rle_lossless.dcm")

Implicitly changing the compression on an already compressed dataset is not currently supported, however it can still be done by decompressing prior to calling compress(). In the example below, a matching image data handler for the original transfer syntax - JPEG 2000 Lossless - is required.

# Requires a JPEG 2000 compatible image data handler
ds = examples.jpeg2k
ds.decompress()
ds.compress(RLELossless)
ds.save_as("US1_RLE.dcm")

Compressing using third-party packages

If you need to perform pixel data compression using an encoding method not supported by pydicom - such as ISO/IEC 10918-1 JPEG - then you’ll need to find a third-party package or application to do so. Once you’ve done that you have to follow the requirements for compressed Pixel Data in the DICOM Standard:

  • Each frame of pixel data must be encoded separately

  • All the encoded frames must then be encapsulated using a basic offset table. When the amount of encoded data is too large for the basic offset table then the use of the extended offset table is recommended.

  • A dataset with encapsulated pixel data must use explicit VR little endian encoding

See the relevant sections of the DICOM Standard for more information.

from typing import List, Tuple

from pydicom import examples
from pydicom.encaps import encapsulate, encapsulate_extended
from pydicom.uid import JPEGBaseline8Bit

# Fetch an example dataset
ds = examples.ct

# Use third-party package to compress
# Let's assume it compresses to JPEG Baseline (lossy)
frames: List[bytes] = third_party_compression_func(...)

# Set the *Transfer Syntax UID* appropriately
ds.file_meta.TransferSyntaxUID = JPEGBaseline8Bit

# Basic encapsulation
ds.PixelData = encapsulate(frames)

# Set the element's VR and use an undefined length
ds["PixelData"].is_undefined_length = True
ds["PixelData"].VR = "OB" if ds.BitsAllocated <= 8 else "OW"

# Save!
ds.save_as("ct_compressed_basic.dcm")

# Extended encapsulation
result: Tuple[bytes, bytes, bytes] = encapsulate_extended(frames)
ds.PixelData = result[0]
ds.ExtendedOffsetTable = result[1]
ds.ExtendedOffsetTableLength = result[2]
ds.save_as("ct_compressed_ext.dcm")