Habitat Analysis: Biomedical Imaging Toolkit (HABIT)

Tumor habitat analysis and intratumoral heterogeneity quantification for clinical and radiomics research. Workflows are driven by YAML configs: preprocessing, habitat segmentation, feature extraction, and optional machine learning.

Language / 语言：English | 简体中文

Documentation

Online docs: https://lichao312214129.github.io/HABIT

Local build: cd docs && make html → docs/build/html/index.html

Suggested learning path

Workflow chapters

Tools & more

Bundled config templates

After cloning or unpacking the repo, use the config/ folder at the project root (sibling to the habit/ Python package). See config/README_CONFIG.md and Configuration reference.

Install & demo data

Python 3.10–3.14. Full steps: Installation.

conda create -n habit python=3.10 -y
conda activate habit
pip install -U pip
pip install habitat-analysis -i https://pypi.org/simple
habit --version
# import name: import habit

Optional: napari for habit view (see Installation). PyRadiomics is separate when you need radiomics. Other capabilities are extras — missing ones raise OptionalDependencyError with the exact pip install command, e.g.:

pip install "habitat-analysis[ml,analysis]"

• Source: GitHub (dev: pip install -e .)
• Demo data: Quickstart

Support & citation

• Issues: GitHub Issues
• Citation: see CITATION.cff
• License: Apache License 2.0. Free for academic and commercial use; the only obligation is to retain the copyright and license notices and to ship NOTICE with redistributions. When HABIT supports scientific work, the authors request -- but do not require as a license condition -- that you cite it