bioMONAI is a low-code Python-based platform for developing and deploying deep learning models in biomedical imaging built on top of the MONAI framework, fastai, and TorchIO. This project aims to facilitate interoperability, reproducibility, and community collaboration in biomedical research.

• bioMONAI
  • Overview
  • Table of Contents
  • Installation
  • Getting Started
  • Usage
  • Contributing
  • License
  • Contact

To install the bioMONAI environment, follow these steps:

1. Clone the repository:

   git clone https://github.com/deepclem/biomonai.git
   cd biomonai

2. Create a new Conda environment and install dependencies:

   conda env create --file bioMONAI-env.yml

3. Activate the environment and install MONAI:

   conda activate bioMONAI-env
   pip install -e .

To get started with bioMONAI, we recommend exploring our tutorials, which guide you through model training for various tasks such as classification and denoising.

Notebook	Open in Colab
Tutorial: Classification 2D This notebook provides a comprehensive guide on training deep learning models for 2D image classification tasks, covering data loading, preprocessing, model building, training, and evaluation.
Tutorial: Denoising 2D This notebook offers a detailed guide on applying deep learning techniques to denoise biological microscopy images. It covers data preparation, model architecture, training processes, and evaluation methods, providing a comprehensive resource for enhancing image quality in biological research.

To use bioMONAI for your own projects, follow these steps:

1. Create a new Jupyter notebook or open an existing one.

2. Import necessary modules:

   import bioMONAI

3. Start coding! You can now leverage MONAI’s capabilities alongside the interactive features of Jupyter notebooks.

We welcome contributions from the community! To contribute to BioMONAI nbs, follow these steps:

1. Fork the repository on GitHub.

2. Clone your fork:

   git clone https://github.com/your_username/biomonai.git
   cd biomonai

3. Create a new Conda environment and install dependencies:

   conda env create --file bioMONAI-env.yml

4. Create a new branch for your changes:

   git checkout -b feature/new-feature

5. Activate the environment and install MONAI in dev mode:

   conda activate bioMONAI-env
   pip install -e .[dev]

6. Make your changes and commit them:

   git add .
   git commit -m "Add new feature: <feature description>"

7. Push to your fork and create a pull request on GitHub.

8. Wait for the review, and merge if everything looks good!

bioMONAI is released under the Apache 2.0 license. See LICENSE for more details.

If you have any questions or need further assistance, please open an issue on GitHub or contact us directly at:

• Project Lead: Biagio Mandracchia
• Contributors: Sara Cruz-Adrados, Juan Pita-López, Rosa-María Menchón-Lara