pylibjpeg-rle 2.2.0

Python bindings for a fast RLE decoder/encoder, with a focus on use as a plugin for pylibjpeg

pylibjpeg-rle

A fast DICOM (PackBits) RLE plugin for pylibjpeg, written in Rust with a Python wrapper.

Linux, MacOS and Windows are all supported.

Installation

Installing the current release

pip install pylibjpeg-rle

Installing the development version

Make sure Python, Git and Rust are installed. For Windows, you also need to install Microsoft's C++ Build Tools.

git clone https://github.com/pydicom/pylibjpeg-rle
cd pylibjpeg-rle
python -m pip install .

Supported Transfer Syntaxes

UID	Description	Decoding	Encoding
1.2.840.10008.1.2.5	RLE Lossless	Yes	Yes

Usage

Decoding

With pylibjpeg

from pydicom import dcmread
from pydicom.data import get_testdata_file

ds = dcmread(get_testdata_file("OBXXXX1A_rle.dcm"))
arr = ds.pixel_array

Standalone with pydicom

Alternatively you can use the included functions to decode a given dataset:

from rle import pixel_array, generate_frames

# Return the entire Pixel Data as an ndarray
arr = pixel_array(ds)

# Generator function that only processes 1 frame at a time,
# may help reduce memory usage when dealing with large Pixel Data
for arr in generate_frames(ds):
    print(arr.shape)

Encoding

Standalone with pydicom

Convert uncompressed pixel data to RLE encoding and save:

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

from rle import pixel_data

# Get the uncompressed pixel data
ds = dcmread(get_testdata_file("OBXXXX1A.dcm"))
arr = ds.pixel_array

# RLE encode and encapsulate `arr`
ds.PixelData = pixel_data(arr, ds)
# Set the correct *Transfer Syntax UID*
ds.file_meta.TransferSyntaxUID = RLELossless
ds.save_as('as_rle.dcm')

Benchmarks

Decoding

Time per 1000 decodes, pydicom's default RLE decoder vs. pylibjpeg-rle:

Dataset	Pixels	Bytes	pydicom	pylibjpeg-rle
OBXXXX1A_rle.dcm	480,000	480,000	5.7 s	1.1 s
OBXXXX1A_rle_2frame.dcm	960,000	960,000	11.5 s	2.1 s
SC_rgb_rle.dcm	10,000	30,000	0.28 s	0.19 s
SC_rgb_rle_2frame.dcm	20,000	60,000	0.45 s	0.28 s
MR_small_RLE.dcm	4,096	8,192	0.46 s	0.15 s
emri_small_RLE.dcm	40,960	81,920	1.8 s	0.67 s
SC_rgb_rle_16bit.dcm	10,000	60,000	0.48 s	0.25 s
SC_rgb_rle_16bit_2frame.dcm	20,000	120,000	0.86 s	0.39 s
rtdose_rle_1frame.dcm	100	400	0.16 s	0.13 s
rtdose_rle.dcm	1,500	6,000	1.0 s	0.64 s
SC_rgb_rle_32bit.dcm	10,000	120,000	0.82 s	0.35 s
SC_rgb_rle_32bit_2frame.dcm	20,000	240,000	1.5 s	0.60 s

Encoding

Time per 1000 encodes, pydicom's default RLE encoder vs. pylibjpeg-rle and python-gdcm:

Dataset	Pixels	Bytes	pydicom	pylibjpeg-rle	python-gdcm
OBXXXX1A.dcm	480,000	480,000	30.6 s	1.4 s	1.5 s
SC_rgb.dcm	10,000	30,000	1.9 s	0.11 s	0.21 s
MR_small.dcm	4,096	8,192	3.0 s	0.11 s	0.29 s
SC_rgb_16bit.dcm	10,000	60,000	3.6 s	0.18 s	0.28 s
rtdose_1frame.dcm	100	400	0.28 s	0.04 s	0.14 s
SC_rgb_32bit.dcm	10,000	120,000	7.1 s	0.32 s	0.43 s