## NVIDIA NIM for MAISI
MAISI (Medical AI for Synthetic Imaging) is a state-of-the-art three-dimensional (3D) Latent Diffusion Model designed for generating high-quality synthetic CT images with or without anatomical annotations. This AI model excels in data augmentation and creating realistic medical imaging data to supplement limited datasets due to privacy concerns or rare conditions. It can also significantly enhance the performance of other medical imaging AI models by generating diverse and realistic training data.

This container, which includes the MAISI model, is powered by NVIDIA NIM, part of NVIDIA AI Enterprise. This integration offers a suite of easy-to-use microservices designed to accelerate the deployment of AI models, like MAISI, across cloud, data centers, and workstations.

### Key Features of MAISI:

- Generates high-resolution 3D CT images up to 512 × 512 × 768 voxels
- Supports variable voxel sizes ranging from 0.5mm to 3.0mm
- Capable of annotating up to 127 anatomical classes, including organs and tumors
- Allows controllable anatomy size for 10 specific classes
- Produces paired segmentation masks

By providing these capabilities, MAISI is a valuable tool for researchers advancing AI applications in healthcare. However, it is important to note that this model is intended for research purposes only and not for clinical usage.

## What is NVIDIA NIM?
NVIDIA NIM, part of NVIDIA AI Enterprise, is a set of easy-to-use microservices designed to accelerate deployment of generative AI across cloud, data center, and workstations. The MAISI implementation leverages these capabilities to provide comprehensive benefits:

### Enterprise Features

- Deploy anywhere while maintaining control of AI applications and data
- Industry-leading latency and throughput for cost-effective scaling
- Enterprise-grade software with dedicated feature branches and robust validation
- Support for custom model training on domain-specific data

### Development Benefits

- Build and deploy AI applications in minutes rather than weeks
- Standardized APIs and tools optimized for enterprise environments
- Consistent environments across deployment platforms
- Flexible scaling from research projects to production deployments
- Prebuilt containers offering immediate deployment options

By leveraging these capabilities, developers can focus more on innovation and less on deployment complexities, ensuring a smoother and more efficient workflow.

## Ethical Considerations

NVIDIA believes Trustworthy AI is a shared responsibility and we have established policies and practices to enable development for a wide array of AI applications. When downloaded or used in accordance with our terms of service, developers should work with their supporting model team to ensure this model meets requirements for the relevant industry and use case and addresses unforeseen product misuse. For more detailed information on ethical considerations for this model, please see the Model Card++ Explainability, Bias, Safety & Security, and Privacy Subcards. Please report security vulnerabilities or NVIDIA AI Concerns [here](https://www.nvidia.com/en-us/support/submit-security-vulnerability/).

## Getting Started with MAISI NIM
For detailed implementation guidance, visit the [MAISI NIM Documentation](https://docs.nvidia.com/nim/index.html#monai).

## Security Vulnerabilities in Open Source Packages

Please review the [Security Scanning tab](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/maisi/security) to view the latest security scan results.

For certain open-source vulnerabilities listed in the scan results, NVIDIA provides a response in the form of a Vulnerability Exploitability eXchange (VEX) document. The VEX information can be reviewed and downloaded from the [Security Scanning tab](https://catalog.ngc.nvidia.com/orgs/nim/teams/nvidia/containers/maisi/security).

## Get Help

### Enterprise Support

Get access to knowledge base articles and support cases or [submit a ticket](https://www.nvidia.com/en-us/data-center/products/ai-enterprise-suite/support/).

### NVIDIA AI Enterprise Documentation

Visit the [NVIDIA AI Enterprise Documentation Hub](https://docs.nvidia.com/ai-enterprise/) for release documentation, deployment guides and more.


## Governing Terms
The NIM container is governed by [NVIDIA Agreements | Enterprise Software | NVIDIA Software License Agreement](https://www.nvidia.com/en-us/agreements/enterprise-software/nvidia-software-license-agreement/) and [NVIDIA Agreements | Enterprise Software | Product Specific Terms for AI Product](https://www.nvidia.com/en-us/agreements/enterprise-software/product-specific-terms-for-ai-products/); and the use of this model is governed by the [ai-foundation-models-community-license.pdf](https://docs.nvidia.com/ai-foundation-models-community-license.pdf) .

**You are responsible for ensuring that your use of NVIDIA AI Foundation Models complies with all applicable laws.**

maisi

MAISI NIM generated high-quality synthetic CT images with or without anatomical annotations.