frankkramer-lab/MIScnn
Open-source Python library for 2D/3D medical image segmentation using deep learning CNN models.
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MIScnn provides an intuitive API for setting up medical image segmentation pipelines with state-of-the-art convolutional neural networks. It handles data I/O, preprocessing, and data augmentation for biomedical images, and supports patch-wise and full image analysis. The library includes built-in deep learning models and metrics, multiple evaluation techniques like cross-validation, and is built on Keras with TensorFlow as the backend.
Frequently asked
- What is frankkramer-lab/MIScnn?
- Open-source Python library for 2D/3D medical image segmentation using deep learning CNN models.
- Is MIScnn open source?
- Yes — frankkramer-lab/MIScnn is open source, released under the GPL-3.0 license.
- What language is MIScnn written in?
- frankkramer-lab/MIScnn is primarily written in Python.
- How popular is MIScnn?
- frankkramer-lab/MIScnn has 425 stars on GitHub.
- Where can I find MIScnn?
- frankkramer-lab/MIScnn is on GitHub at https://github.com/frankkramer-lab/MIScnn.