histomil
A Python package for handling histopathology whole-slide images using multiple instance learning (MIL) techniques.
Science Score: 44.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
✓CITATION.cff file
Found 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 (16.2%) to scientific vocabulary
Keywords
Repository
A Python package for handling histopathology whole-slide images using multiple instance learning (MIL) techniques.
Basic Info
Statistics
- Stars: 29
- Watchers: 2
- Forks: 7
- Open Issues: 2
- Releases: 2
Topics
Metadata Files
README.md
HistoMIL

Author: Shi Pan, UCL Genetics Institute
HistoMIL is a Python package for handling histopathology whole-slide images using multiple instance learning (MIL) techniques. With HistoMIL, you can create MIL datasets, train and evaluate MIL models, and make MIL predictions on new slide images.
Getting Started
To use HistoMIL, you first need to create a conda environment with the required dependencies.
create env with pre-defined file
You can do this by importing the env.yml file provided in this repository:
linux user pre-requisites
- Create conda env
bash conda create -n HistoMIL python=3.9This will create a new environment named histomil, which you can activate with:
bash
conda activate HistoMIL
windows user pre-requisites
Windows (10+) 1. Download OpenSlide binaries from this page. Extract the folder and add bin and lib subdirectories to Windows system path. If you are using a conda environment you can also copy bin and lib subdirectories to [Anaconda Installation Path]/envs/YOUR ENV/Library/.
- Install OpenJPEG. The easiest way is to install OpenJpeg is through conda using
bash
conda create -n HistoMIL python=3.9
This will create a new environment named histomil, which you can activate with:
bash
conda activate HistoMIL
bash
C:\> conda install -c conda-forge openjpeg
macOS user pre-requisites
On macOS there are two popular package managers, homebrew and macports.
Homebrew
bash
brew install openjpeg openslide
MacPorts
bash
port install openjpeg openslide
create env manually
Then install openslide and pytorch-gpu with following scripts.
bash
conda install -c conda-forge openslide
conda install pytorch pytorch-cuda=11.7 -c pytorch -c nvidia
Next, install the required Python packages with pip:
bash
pip install -r requirements.txt
This will install all the packages listed in requirements.txt, including HistoMIL itself.
Usage
All of the examples for using HistoMIL are included in the Notebooks folder. You can open and run these Jupyter notebooks to see how to use HistoMIL for different histopathology tasks.
Contributing
If you find a bug or want to suggest a new feature for HistoMIL, please open a GitHub issue in this repository. Pull requests are also welcome!
License
HistoMIL is released under the GNU-GPL License. See the LICENSE file for more information.
Owner
- Name: Secrier Lab @ UCL Genetics Institute
- Login: secrierlab
- Kind: organization
- Location: University College London, UK
- Website: https://secrierlab.github.io/
- Repositories: 1
- Profile: https://github.com/secrierlab
Citation (CITATION.cff)
cff-version: 1.0.0 message: "If you use this software, please cite it as below." authors: - family-names: "Pan" given-names: "Shi" - family-names: "Secrier" given-names: "Maria" title: "HistoMIL: a Python package for training Multiple Instance Learning models on histopathology slides." version: 1.0.0 date-released: 2023-08-07 url: "https://github.com/secrierlab/HistoMIL"
GitHub Events
Total
- Watch event: 3
- Pull request event: 2
Last Year
- Watch event: 3
- Pull request event: 2
Issues and Pull Requests
Last synced: 7 months ago
All Time
- Total issues: 0
- Total pull requests: 2
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Total issue authors: 0
- Total pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Past Year
- Issues: 0
- Pull requests: 2
- Average time to close issues: N/A
- Average time to close pull requests: N/A
- Issue authors: 0
- Pull request authors: 1
- Average comments per issue: 0
- Average comments per pull request: 0.0
- Merged pull requests: 0
- Bot issues: 0
- Bot pull requests: 0
Top Authors
Issue Authors
- jeginderof (1)
Pull Request Authors
- awxlong (2)