landmarker 0.1.0

A PyTorch-based toolkit for (anatomical) landmark detection in images.

Landmarker is a PyTorch-based toolkit for (anatomical) landmark detection in images. It is designed to be easy to use and to provide a flexible framework for state-of-the-art landmark detection algorithms for small and large datasets. Landmarker was developed for landmark detection in medical images. However, it can be used for any type of landmark detection problem.

🛠️ Installation

	command
pip	pip install landmarker

🚀 Getting Started

Technical documentation is available at documentation.

Examples and tutorials are available at examples

✨ Features

• Modular: Landmarker is designed to be modular. It is easy to add new models, datasets, and loss functions.
• Flexible: Landmarker provides a flexible framework for landmark detection. It is easy to customize the training and evaluation process.
• Easy to use: Landmarker is easy to use. It provides a simple API for training and evaluation.
• State-of-the-art: Landmarker provides state-of-the-art landmark detection models and loss functions.

📈 Future Work

• Extension to 3D landmark detection.
• Extension to landmark detection in videos.
• Add uncertainty estimation.
• ...

👪 Contributing

We welcome contributions to Landmarker. Please read the contributing guidelines for more information.

📖 Citation

If you use Landmarker in your research, please cite the following paper:

SCIENTIFIC PAPER UNDER REVIEW

📝 License

Landmark is licensed under the IMEC license.

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👤 Jef Jonkers