Compressing Pixel Data

How to compress Pixel Data

Compressing using third-party packages

Because pydicom currently offers limited support for compressing Pixel Data you’ll have to rely on third-party packages to perform the actual compression. pydicom can then be used to take that compressed data and add it to the dataset.

The requirements for compressed Pixel Data in the DICOM Standard are:

• 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 dcmread
from pydicom.data import get_testdata_file
from pydicom.encaps import encapsulate, encapsulate_extended
from pydicom.uid import JPEG2000Lossless

path = get_testdata_file("CT_small.dcm")
ds = dcmread(path)

# Use third-party package to compress
# Let's assume it compresses to JPEG 2000 (lossless)
frames: List[bytes] = third_party_compression_func(...)

# Set the *Transfer Syntax UID* appropriately
ds.file_meta.TransferSyntaxUID = JPEG2000Lossless
# For *Samples per Pixel* 1 the *Photometric Interpretation* is unchanged

# Basic encapsulation
ds.PixelData = encapsulate(frames)

# Set the dataset encoding
ds.is_little_endian = True
ds.is_implicit_VR = False

# Save!
ds.save_as("CT_small_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_small_compressed_ext.dcm")

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
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

Compressing with Dataset.compress()

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

from pydicom.data import get_testdata_file
from pydicom.uid import RLELossless

ds = get_testdata_file("CT_small.dcm", read=True)
ds.compress(RLELossless)
ds.save_as("CT_small_rle.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_small_rle.dcm")

Implicitly changing the compression on an already compressed dataset is not currently supported, however it can still be done explicitly 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 = get_testdata_file("US1_J2KR.dcm", read=True)
arr = ds.pixel_array
ds.PhotometricInterpretation = 'RGB'
ds.compress(RLELossless, arr)
ds.save_as("US1_RLE.dcm")

Note that the Photometric Interpretation in this case has been changed from 'YBR_RCT', which is the value for when it’s J2K compressed, to 'RGB' which is the correct value for this particular dataset once the Pixel Data is RLE compressed. It’s up to you to ensure that the the correct Photometric Interpretation has been set and that the decompressed pixel data is in the correct color space prior to actually calling compress().