#MONAI

MONAI, built on PyTorch, is an open-source framework designed for deep learning in medical imaging. It offers state-of-the-art workflows with flexible pre-processing, compositional APIs, and domain-specific tools. Supporting multi-GPU environments, MONAI promotes collaboration among researchers. Its Model Zoo and extensive documentation streamline integration and use, making MONAI a valuable resource in healthcare.

Discover a wide array of MONAI tutorials for incorporating deep learning into medical imaging processes. Includes examples on 2D and 3D tasks like classification, segmentation, and regression using PyTorch. Understand the use of platforms such as Jupyter Notebook and Colab, as well as leveraging GPU resources. Also covers experiment management, federated learning, digital pathology, and deployment strategies using BentoML, Ray, and Triton, providing valuable insights for both novice and experienced practitioners in medical imaging.