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NVIDIA Introduces Hosted MONAI: Streamlining Medical Imaging AI

NVIDIA Introduces Hosted MONAI: Streamlining Medical Imaging AI

The NVIDIA MONAI cloud APIs introduce user-friendly annotation and training capabilities tailored for medical imaging, addressing the complexities in developing efficient and cost-effective AI solutions in this domain. Establishing a solid foundation for domain-specialized development, these APIs offer comprehensive software stack optimizations, scalable multi-node systems, and cutting-edge research advancements. Crucially, they tackle the challenge of acquiring high-quality ground-truth data, especially for intricate 3D medical images that demand specialized expertise for annotation.

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The VISTA-3D (Vision Imaging Segmentation and Annotation) foundation model is at the heart of these APIs and is engineered for continuous learning. This unique capability empowers AI models to enhance performance based on user feedback and new data, streamlining the creation.

Medical imaging solution providers and machine learning platforms are tapping into the potential of NVIDIA MONAI cloud APIs to deliver vital AI insights, expediting their customers’ workflows.

Utilizing MONAI through NVIDIA AI Enterprise, Flywheel now incorporates MONAI cloud APIs to hasten medical image curation, labeling analysis, and training. Their cloud-based platform enables biopharma companies, life science organizations, healthcare providers, and academic medical centers to efficiently curate and train medical imaging data, expediting AI model development.

Dan Marcus, Chief Scientific Officer at Flywheel, highlighted, “NVIDIA MONAI cloud APIs significantly reduce the expense of constructing high-quality AI models for radiology, disease research, and clinical trial data evaluation.” Adding cloud APIs for interactive annotation and automated segmentation accelerates AI model development, empowering the delivery of innovative solutions.

Annotation and viewer solution providers, such as Redbrick AI, Radical Imaging, V7 Labs, and Centaur Labs, leverage NVIDIA MONAI cloud APIs to expedite AI-assisted annotation and training capabilities. Redbrick AI, for instance, integrates VISTA-3D models to facilitate interactive cloud annotation for medical device customers, streamlining model building across various clinical applications.

Shivam Sharma, CEO of RedBrick AI, emphasized, “VISTA-3D enables rapid model building across diverse clinical applications, ensuring accurate and reliable segmentation outcomes.”

Moreover, MLOps platform builders like Dataiku, ClearML, and Weight & Biases are exploring the integration of NVIDIA MONAI cloud APIs to streamline enterprise AI model development. Dataiku aims to leverage these APIs to simplify AI model creation for medical imaging applications, making sophisticated segmentation models accessible through a low-code option, thereby democratizing AI in biomedical imaging.

Kelci Miclaus, Global Head of AI Health and Life Sciences Solutions at Dataiku, highlighted, “NVIDIA MONAI cloud APIs democratize AI by empowering data and domain experts to create and deploy AI-driven workflows effortlessly.”

FAQs

1. How are medical imaging solution providers leveraging these APIs?
Companies like Flywheel utilize MONAI cloud APIs to expedite medical image curation, labeling analysis, and training. This accelerates AI model development for biopharma, life sciences, healthcare providers, and academic medical centers.

2. What role do annotation and viewer solution providers play in utilizing these APIs?
Annotation and viewer solution providers, such as Redbrick AI, Radical Imaging, V7 Labs, and Centaur Labs, use NVIDIA MONAI cloud APIs for AI-assisted annotation and training capabilities. These tools facilitate model building across diverse clinical applications, ensuring accurate segmentation outcomes.

3. How do MLOps platform builders integrate these APIs for AI model development?
MLOps platform builders like Dataiku, ClearML, and Weight & Biases are exploring the integration of NVIDIA MONAI cloud APIs to streamline AI model development for medical imaging. This integration aims to democratize AI by making sophisticated segmentation models accessible through low-code options, empowering data and domain experts.

4. What benefits do these APIs offer regarding cost and efficiency in AI model construction for medical imaging?
NVIDIA MONAI cloud APIs significantly reduce the cost of constructing high-quality AI models for radiology, disease research, and clinical trial data evaluation. They expedite model development, leading to innovative solutions for various clinical applications.

[To share your insights with us, please write to sghosh@martechseries.com]

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