[Updating News (2024.02.03)]

1. Updated Part "Troubleshooting"

[Updating News (2023.12.26)]

1. sdpc-linux and sdpc-win are no longer be updated. The latest library sdpc-for-python is a new version for Sdpc Python library, which can be used in both Windows and Linux Systems.
2. The color correction has been updated. Now the color of the cropped patches are consistent with the color in the reading software.
3. Changed function name level_downsample to level_downsamples.
4. Chineses paths have been supported.
5. Added a function to view the magnification directly: wsi.scan_magnification().
6. Added a function to view the sampling ratio directly：wsi.sampling_rate().
7. Added a function of obtaining the thumbnail image: wsi.get_thumbnail(thumbnail_level).
8. The wsi.crop_patches() function has been added. Now you can call the function directly in the code to separate the foreground tissue area and crop the patches (Using Pillow Library to save patches).
9. Added a option that can normalize images in wsi.crop_patches() function, it normalizes by H and E channels.

About sdpc-for-python

Sdpc-for-python is a python library for processing whole slide images (WSIs) in sdpc format. To read WSIs in sdpc format in Windows platform, download the TEKSQRAY reading software.

Download link	Extraction code	Instruction
Baidu Cloud	sq12	Lite version
Tsinghua Cloud	-	Full version

Installation

Platform	PyPI installer
Windows/Linux	pip install sdpc-for-python

How to use Sdpc library

• Import Sdpc Library:

import sdpc

• Read the WSI

wsi = sdpc.Sdpc(wsi_path)

• Get the number of levels of the WSI

level_count = wsi.level_count

• By how much are levels downsampled from the original image?

level_downsamples = wsi.level_downsamples

• Get the dimensions of data in each level

level_dimensions = wsi.level_dimensions

• Get the patch under a certain position at a certain level in the WSI

img = wsi.read_region((Position_X, Position_Y), patch_level, (size_H, size_W))   # patch_size = (size_H, size_W)

• Obtain the thumbnail (numpy format)

thumbnail_np = wsi.get_thumbnail(thumbnail_level)

thumbnail_level: the level of the wanted thumbnail

• Obtain the scaned magnification

magnification = wsi.scan_magnification()

• Obtain the downsampling ratio

ration = wsi.sampling_rate()

• Crop the foreground tissue to obtain the patches automatically

wsi.crop_patches(tile_size, overlap_size, patch_level, save_dir, blank_TH=0.7, is_mark=True, is_mask=True, patch_norm=False)

tile_size: patch size

overlap_size: overlapped size: recommend: 0

save_dir: path to save

blank_TH: crop patches with blank rate lower than blank_TH, recommend: 0.7, default=0.7

is_mark: whether the marked thumbnail is needed, default=True

is_mask: whether the mask of the marked thumbnail is needed, default=True

patch_norm: whether the normalized color of patches is needed, default=False. (select this will reduce time greatly)

Demo code of using Sdpc and OpenSlide library to crop the patches

Using Sdpc library to crop patches.

python sdpc_crop_patches.py

Using OpenSlide library to crop patches.

python openslide_crop_patches.py

Other method to cut patches with Sdpc Library

• Multi-thread processing

Build patches from WSIs in sdpc format in Build-patch-for-sdpc repository.

Two approaches (build w/wo .sdpl) to build patches are given for two different platforms (Windows/Linux).

Troubleshooting

1. OSError: libDecodeHevc.so: cannot open shared object file: No such file or directory

See the issue #2.

2. OSError: version 'GLIBC_2.33' not found

See the issue #12.

Jiawen Li, H&G Pathology AI Research Team