🌟opensdpc: library for histopathology whole slide image processing

🔥 Introduction about opensdpc (extended from openslide)

opensdpc is a python library for processing whole slide images (WSIs) in sdpc format extended form openslide library, therefore, opensdpc also supports other common formats such as svs, tiff, ndpi, etc. To read WSIs in sdpc format in Windows platform, download the TEKSQRAY reading software.

🎈Installation

There are several versions available. We recommend Linux users to use the opensdpc version.

🌟 opensdpc (recommend for Linux users) 🌟

• [Optional] install openslide library on Linux (same as openslide)

  apt install openslide-tools
  pip install openslide-python

  If your system has already install the openslide-tools and openslide-python, you can skip this step.

• [Optional] install opensdpc-tools

  wget --content-disposition https://cloud.tsinghua.edu.cn/f/9077d5abb17a4f10b7d6/?dl=1
  dpkg -i opensdpc-tools_1.0-1_all.deb

  You can also download this tool from Tsinghua Cloud. If you want to remove it, sudo dpkg -P opensdpc-tools. \ [Note]: the installation of opensdpc-tools requires root permission, so you need to use sudo -i to install it. If your system has already install the opensdpc-tools, you can skip this step.

• install opensdpc library

  pip install opensdpc

  After this operation, the opensdpc installation is complete.

Some users have no sudo permission on their Linux system. In this case, you can git clone this repository first by git clone https://github.com/WonderLandxD/opensdpc.git, then refer to the following steps to add the opensdpc environment variable:

vim ~/.bashrc
export LD_LIBRARY_PATH=$LD_LIBRARY_PATH:/<repository_path>/LINUX/:/<repository_path>/LINUX/ffmpeg/
source ~/.bashrc

After this operation, you can also import opensdpc library in your python code.

🚀 Basic usage

There are two example WSIs in the data folder, which are in the sdpc format and svs format (download from CLAM) respectively.

We will use the sdpc format WSI as an example to demonstrate how to use basic functions of opensdpc.

import opensdpc

slide = opensdpc.OpenSdpc('data/20220514_145829_0.sdpc') # load the WSI

print(f'This WSI have {slide.level_count} levels.') # the number of levels

print(f'The magnification of this WSI is {slide.scan_magnification}x.') # the magnification of the WSI

print(f'The downsampling ratio of this WSI is {slide.sampling_rate}.') # the downsampling ratio of the WSI

print(f'The downsample ratio of each level is {slide.level_downsamples}.') # the downsample ratio of each level

print(f'The dimensions of each level is {slide.level_dimensions}.') # the dimensions of each level

thumbnail = slide.get_thumbnail(3) # get the thumbnail of the WSI
print(f'The thumbnail (level 3) shape is {thumbnail.shape}.') # the shape of the thumbnail

you will see the result like this:

This WSI have 4 levels.
The magnification of this WSI is 40x.
The downsampling ratio of this WSI is 0.25.
The downsample ratio of each level is (1.0, 4.0, 16.0, 64.0).
The dimensions of each level is ((26880, 21504), (6720, 5376), (1680, 1344), (420, 336)).
The thumbnail (level 3) shape is (336, 420, 3).

🚉 Generate the patches

We provide a demo file to show how to generate the patches from the WSI. See generate_demo.ipynb for more details. Note: when using .ipynb file at the first time, you need install the opensdpc library using pip in Jupyter Notebook, jump to here to see how to do it.

Jiawen Li, H&G Pathology AI Research Team