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

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  • License: GNU General Public License v3 (GPLv3) (MIT)
  • Author: scaramallion
  • Tags dicom, pydicom, python, medicalimaging, radiotherapy, oncology, imaging, radiology, nuclearmedicine, rle, pylibjpeg, rust
  • Requires: Python >=3.7
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Project description

pylibjpeg-rle

A fast DICOM (PackBits) RLE plugin for pylibjpeg, written in Rust with a Python 3.7+ 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 setup.py develop

Supported Transfer Syntaxes

UID Description Decoding Encoding
1.2.840.10008.1.2.5 RLE Lossless Yes Yes

Usage

Decoding

With pylibjpeg

Because pydicom defaults to its own RLE decoder you must specify the use of pylibjpeg when decompressing:

from pydicom import dcmread
from pydicom.data import get_testdata_file

ds = dcmread(get_testdata_file("OBXXXX1A_rle.dcm"))
ds.decompress("pylibjpeg")
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 handler vs. pylibjpeg-rle

Dataset Pixels Bytes pydicom pylibjpeg-rle
OBXXXX1A_rle.dcm 480,000 480,000 4.89 s 0.79 s
OBXXXX1A_rle_2frame.dcm 960,000 960,000 9.89 s 1.65 s
SC_rgb_rle.dcm 10,000 30,000 0.20 s 0.15 s
SC_rgb_rle_2frame.dcm 20,000 60,000 0.32 s 0.18 s
MR_small_RLE.dcm 4,096 8,192 0.35 s 0.13 s
emri_small_RLE.dcm 40,960 81,920 1.13 s 0.28 s
SC_rgb_rle_16bit.dcm 10,000 60,000 0.33 s 0.17 s
SC_rgb_rle_16bit_2frame.dcm 20,000 120,000 0.56 s 0.21 s
rtdose_rle_1frame.dcm 100 400 0.12 s 0.13 s
rtdose_rle.dcm 1,500 6,000 0.53 s 0.26 s
SC_rgb_rle_32bit.dcm 10,000 120,000 0.56 s 0.19 s
SC_rgb_rle_32bit_2frame.dcm 20,000 240,000 1.03 s 0.28 s

Encoding

Time per 1000 encodes, pydicom's default RLE handler vs. pylibjpeg-rle

Dataset Pixels Bytes pydicom pylibjpeg-rle
OBXXXX1A.dcm 480,000 480,000 30.7 s 1.36 s
SC_rgb.dcm 10,000 30,000 1.80 s 0.09 s
MR_small.dcm 4,096 8,192 2.29 s 0.04 s
SC_rgb_16bit.dcm 10,000 60,000 3.57 s 0.17 s
rtdose_1frame.dcm 100 400 0.19 s 0.003 s
SC_rgb_32bit.dcm 10,000 120,000 7.20 s 0.33 s

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  • License: GNU General Public License v3 (GPLv3) (MIT)
  • Author: scaramallion
  • Tags dicom, pydicom, python, medicalimaging, radiotherapy, oncology, imaging, radiology, nuclearmedicine, rle, pylibjpeg, rust
  • Requires: Python >=3.7
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2.0.0

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