Siemens Healthineers has announced its adoption of MONAI Deploy, a significant step towards enhancing the integration of artificial intelligence (AI) workflows into medical imaging solutions.
The collaboration, revealed at the annual meeting of the Radiological Society of North America (RSNA), aims to accelerate the processing and evaluation of the over 3.6 billion medical imaging tests conducted globally each year, including X-rays, CT scans, MRIs, and ultrasounds.
Key highlights include:
MONAI Overview: MONAI (Medical Open Network for AI) is an open-source platform developed by NVIDIA for advancing AI in medical imaging, designed to facilitate collaboration between clinicians and data scientists.
MONAI Deploy: This module acts as a bridge from research to clinical application, allowing users to deploy trained AI models into real-world settings with minimal coding. Its implementation by Siemens Healthineers aims to streamline the integration of AI applications in clinical workflows.
Impact on Clinical Workflows: The integration of MONAI Deploy on Siemens Healthineers platforms, such as Syngo Carbon and syngo.via, has significantly reduced deployment times from months to mere clicks. This enhances accessibility for healthcare institutions striving to leverage new AI advancements.
Enhancements in AI Models: MONAI's latest release (v1.4) features new foundation models for medical imaging, including MAISI and VISTA-3D, which provide capabilities for simulating images and segmenting anatomical structures.
Widespread Adoption: A variety of healthcare organizations, including academic institutions and startups, are leveraging MONAI to develop AI-driven solutions across different medical specialties, enhancing diagnostic accuracy and efficiency in clinical practice.
Cloud Accessibility: MONAI fosters scalable AI solutions through partnerships with major cloud platforms such as AWS HealthImaging, Google Cloud, and Microsoft Cloud for Healthcare, enabling remote deployment and research capabilities.
