MONAI (Medical Open Network for AI) is an open-source domain-specific framework for healthcare and medical imaging research. It offers tools, data structures, and pre-processing capabilities to streamline the development of deep learning models for medical image analysis. With a focus on reproducibility and extensibility, MONAI simplifies data loading, augmentation, training, and evaluation processes, catering to diverse medical imaging tasks such as segmentation, classification, and registration. By providing a specialized platform for medical AI research, MONAI accelerates innovation and collaboration in the field, aiding researchers and practitioners in advancing the accuracy and efficiency of medical image analysis algorithms.

Publish Date

Jul 11, 2023

Topic

  • Artificial Intelligence
  • Generative AI
  • Large Language Models
  • Open Source
  • Research
  • Tech Tools

Audience Type

  • Clinician
  • Developer
  • Imaging IT
  • Researcher/Scientist

Resource

Teaching AI for Radiology Applications: A Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM

Oct 1, 2025

In a groundbreaking collaboration led by the SIIM Machine Learning Education Subcommittee, the American Association of Physicists in Medicine (AAPM), Radiological Society of North America (RSNA), and Society for Imaging Informatics in Medicine (SIIM) are proud to announce the simultaneous co-publication of “Teaching AI for Radiology Applications: A Multisociety-Recommended Syllabus from the AAPM, ACR, RSNA, and SIIM” in these three flagship journals: Medical Physics, Radiology: Artificial Intelligence, and the Journal of Imaging Informatics in Medicine (JIIM).

The society-endorsed syllabus outlines critical competencies for four key groups: clinical users, technology purchasers, clinical collaborators, and AI developers. Designed as a flexible framework, it allows institutions to adapt content while ensuring consistent instruction on AI fundamentals, clinical integration, regulatory requirements, and ethical considerations.

Resource

Multi-Agent AI and Ethics in Radiology: Navigating the Trust Crisis in Advanced Medical Systems
(Part 1)

Sep 9, 2025

Part 1: The Medical AI Background: From Simple Tools to Complex Systems Picture this: you’re a radiologist examining a chest…

Resource

Multi-Agent AI and Ethics in Radiology: Navigating the Trust Crisis in Advanced Medical Systems
(Part 2)

Sep 9, 2025

Part 2: Framework, Regulation & Future Directions Additions Ethical Considerations in Medical AI Deployment The deployment of multi-agent AI systems…