tissueloc

tissueloc: Whole slide digital pathology image tissue localization - Published in JOSS (2019)

https://github.com/pingjunchen/tissueloc

Science Score: 93.0%

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    Found 8 DOI reference(s) in README and JOSS metadata
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    Published in Journal of Open Source Software

Keywords

computational-pathology pathology pathology-image python tissue-localization whole-slide-imaging

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ode graph-generation mesh pypi
Last synced: 4 months ago · JSON representation

Repository

Whole Slide Digital Pathology Image Tissue Localization

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Topics
computational-pathology pathology pathology-image python tissue-localization whole-slide-imaging
Created about 7 years ago · Last pushed about 2 years ago
Metadata Files
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README.md

tissueloc: Whole slide digital pathology image tissue localization

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Please consider star this repo if you find tissueloc to be helpful for your work.

Installation

  1. Install OpenSlide. $ sudo apt-get install openslide-tools
  2. Installing Python dependencies. $ pip install scikit-image==0.14.2 $ pip install opencv-python==4.1.2.30 $ pip install openslide-python==1.1.1
  3. Install tissueloc. $ pip install tissueloc==2.1.0

Usage example

Interface

def locate_tissue_cnts(slide_path, max_img_size=2048, smooth_sigma=13, thresh_val = 0.80, min_tissue_size=10000): """ Locate tissue contours of whole slide image Parameters ---------- slide_path : valid slide path The slide to locate the tissue. max_img_size: int Max height and width for the size of slide with selected level. smooth_sigma: int Gaussian smoothing sigma. thresh_val: float Thresholding value. min_tissue_size: int Minimum tissue area. Returns ------- cnts: list List of all contours coordinates of tissues. d_factor: int Downsampling factor of selected level compared to level 0 """

Demo

Testing slide can be downloaded from Figshare. ``` import tissueloc as tl slide_path = "../data/SoftTissue/TCGA-B9EB312E82F6.svs"

locate tissue contours with default parameters

cnts, dfactor = tl.locatetissuecnts(slidepath, maximgsize=2048, smoothsigma=13, threshval=0.80,mintissuesize=10000) ```

Documentation

Hosted in https://tissueloc.readthedocs.io, powered by readthedocs and Sphinx.

Contributing

tissueloc is an open source project and anyone is welcome to contribute. An easy way to get started is by suggesting a new enhancement on the Issues. If you have found a bug, then either report this through Issues, or even better, make a fork of the repository, fix the bug and then create a Pull Requests to get the fix into the master branch.

We would like to test this package on more diversified digital slides. Slides (low level images would be better) and their corresponding results are also very welcome as Pull Requests.

License

tissueloc is free software made available under the MIT License. For details see the LICENSE file.

Contributors

See the AUTHORS.md file for a complete list of contributors to the project.

Citing

tissueloc is published in the Journal of Open Source Software - please consider cite if it's useful for your research: @article{chen2019tissueloc, author = {Pingjun Chen and Lin Yang}, title = {tissueloc: Whole slide digital pathology image tissue localization}, journal = {J. Open Source Software}, volume = {4}, number = {33}, pages = {1148}, year = {2019}, url = {https://doi.org/10.21105/joss.01148}, doi = {10.21105/joss.01148} }

Owner

  • Name: Pingjun Chen
  • Login: PingjunChen
  • Kind: user
  • Location: Houston, Texas
  • Company: MD Anderson Cancer Center

Biomedical Researcher

JOSS Publication

tissueloc: Whole slide digital pathology image tissue localization
Published
January 02, 2019
Volume 4, Issue 33, Page 1148
Authors
Pingjun Chen ORCID
J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida
Lin Yang
J. Crayton Pruitt Family Department of Biomedical Engineering, University of Florida
Editor
Pjotr Prins ORCID
Tags
whole slide image digital pathology tissue localization tissue detection tissue region pyramid structure

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Dependencies

requirements.txt pypi
  • Pillow ==8.3.2
  • numpy ==1.16.2
  • opencv-python ==4.2.0.32
  • openslide-python ==1.1.1
  • scikit-image ==0.14.2
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setup.py pypi
tissueloc/setup.py pypi