MONAI for AMD ROCm documentation#
2025-10-08
2 min read time
The Medical Open Network for AI (MONAI) is a domain-optimized, open-source framework based on PyTorch, explicitly designed for deep learning in healthcare imaging. MONAI 1.0.0 for AMD ROCm is a HIP port of MONAI upstream version 1.5.0. It is API-compatible with upstream MONAI without requiring any code changes.
MONAI for AMD ROCm, a ROCm-enabled version of MONAI, is built on top of PyTorch for AMD ROCm, helping healthcare and life science innovators to leverage GPU acceleration with AMD Instinct GPUs for high-performance inference and training of medical AI applications.
MONAI for AMD ROCm offers open, scalable, and high-performance solutions for life science and healthcare workloads.
The MONAI for AMD ROCm key features include:
Flexible preprocessing for multidimensional medical imaging data
Compositional and portable APIs for smooth integration into existing workflows
Domain-specific implementations for networks, losses, evaluation metrics, and more
Customizable design according to user expertise
Note
MONAI for AMD ROCm is in an early access state. Running production workloads is not recommended.
The code is open and hosted at ROCm-LS/monai.
The documentation is structured as follows:
To contribute to MONAI for AMD ROCm, refer to Contributing to MONAI for AMD ROCm.
You can find licensing information on the Licensing page.