Data

Tools

Indexes

Applications

Experiments

Open Source Science

https://github.com/chrisklsmith/dl4wsicompression

Exploring Deep Learning Approaches to Whole Slide Image Compression code repository

https://github.com/chrisklsmith/dl4wsicompression

Science Score: 26.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ○
    DOI references
  • ○
    Academic publication links
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (8.6%) to scientific vocabulary
Last synced: 9 months ago · JSON representation

Repository

Exploring Deep Learning Approaches to Whole Slide Image Compression code repository

Basic Info
  • Host: GitHub
  • Owner: chrisklsmith
  • License: gpl-3.0
  • Default Branch: main
  • Size: 14.6 KB
Statistics
  • Stars: 0
  • Watchers: 0
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created 11 months ago · Last pushed 11 months ago
Metadata Files
Readme License

README.md

DL4WSICompression

Exploring Deep Learning Approaches to Whole Slide Image Compression code repository

1) Use git clone to download the files needed for running the experiments. 2) Set up a Python environment with the dependencies from requirements.txt file in order to successfully run the code. 3) Download the 'images.zip' folder from the following link to obtain the WSI files and tiled images for training and testing: https://qubstudentcloud-my.sharepoint.com/:u:/g/personal/3056243adsqubacuk/EXThZoU8R8dCvNG8vw5EuxgBSmXKZRJmRC4-FQObLL2PTw?e=G4s47F 4) Unzip and place the images folder at the base level of the DL4WSICompression folder. 5) Run each model from its .ipynb file.

Code available for all 4 models used in the paper is available in this repo as given in Jupyter notebook format. This can be run in Anaconda Navigator or in VS Code.

Link to the WSI sources from The Cancer Genome Atlas from National Cancer Institute GDC Data Portal for more open source SVS files: https://portal.gdc.cancer.gov/analysis_page?app=Downloads

Link to Histoclean software for file preparation before training to remove tiles with over 50% white space: https://github.com/HistoCleanQUB/HistoClean

Owner

  • Login: chrisklsmith
  • Kind: user

GitHub Events

Total
  • Member event: 1
  • Push event: 3
  • Create event: 2
Last Year
  • Member event: 1
  • Push event: 3
  • Create event: 2