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Hulu-Med is an open-source AI model designed for holistic medical vision-language understanding. It facilitates research and development in medical imaging and diagnostics. The model is available in multiple sizes and can be accessed via Hugging Face and ModelScope. It supports transparent and generalist approaches to medical AI.

nnDetection is a self-configuring framework for 3D medical object detection. It can be applied to new datasets without manual intervention. The tool includes guides for datasets used to develop and evaluate its performance. It is designed for medical image analysis.

3DUnetCNN is a Pytorch 3D U-Net Convolution Neural Network (CNN) designed for medical image segmentation. It facilitates the training and application of deep learning models for medical imaging tasks. The tool is designed to be easy to apply and control for various deep learning models.

ANTsPy is a Python library for medical imaging analysis, featuring algorithms for registration and segmentation. It provides tools for advanced normalization and quantitative analysis of medical images. The library is designed for researchers and specialists in the medical imaging field.

Torchio is a medical imaging processing library for AI applications. It provides tools for image manipulation, augmentation, and analysis. The library is designed to facilitate the development of AI solutions in healthcare. It supports various medical imaging modalities and is useful for researchers and developers in the field.

MedSegDiff is an open-source framework utilizing Diffusion Probabilistic Models for medical image segmentation. It enables the reconstruction of organs and tissues from medical images. The tool is designed for researchers and developers working with medical image analysis and AI in healthcare.