An award aimed at decreasing time from Innovation in AI to Implementation with Impact

Leesburg, VA – September 11, 2020 – The Society for Imaging Informatics in Medicine (SIIM) is part of an Academic, Industry and Society consortium selected to participate in the 2020 National Science Foundation (NSF) Convergence Accelerator program. A two-phase program, the goal of NSF’s convergence accelerator initiative is to support and accelerate use-inspired convergence research in areas of national importance within particular topics (tracks) and the potential for significant national impact.

Bennett Landman, PhD, member of the SIIM Machine Learning Committee, Co-Chair of its Research and Tools Sub-committee, and Professor of Electrical Engineering at Vanderbilt University, is leading the project Track D: Scalable, TRaceable Ai for Imaging Translation: Innovation to Implementation for accelerated Impact (STRAIT I3). The purpose of this initiative is to eliminate technical and societal translation impediments of AI enabled cross-disciplinary innovations for public health.

Principal Investigator (PI), Dr. Landman explains “The aim of STRAIT I3 is to develop a collaborative model-centric AI platform that reduces silos and barriers to translation by dramatically reducing time from idea to test to implement and to facilitate cross-disciplinary collaboration through a common vocabulary for testing and validation.”

The proposal’s intellectual merit is organized around three research thrusts, each addressing an essential challenge to inter-disciplinary translation of model-centric artificial intelligence (AI). One of four Co-PI’s, Vanderbilt University Assistant Professor Ipek Oguz, PhD, explains “New informatics technologies for scalable validation will be developed to efficiently capture provenance and data annotation, to enhance the validation/peer review process, and to provide robust capabilities for innovation and translation.”

Co-PI Leon Chen, MD, Co-Founder and CEO of Inc adds, “This convergence accelerator proposal builds on SIIM’s active efforts with academic partners and industry over the last two years creating annotated medical imaging datasets, hosting medical imaging AI competitions, and open sourcing the winning solutions in different medical domains.”

Co-PI Steve Langer, PhD, Co-Chair SIIM Machine Learning Committee, Co-Chair Radiology Informatics Division at Mayo Clinic, and co-founder said, “The core team formed from the SIIM Machine Learning Committee, drawing together expertise in: AI / model building, cyber-physical systems and scalable computing, scientific publishing (SIIM’s Journal of Digital Imaging, since 1988), and technology translation to clinical practice via scalable annotation and workflow orchestration (via two technology partners).”

Co-PI Cheryl Kreider Carey, MBA, CAE, SIIM Executive Director summarizes the project, “We will deeply annotate the COVID 19 datasets (data), support/aggregate/release a machine learning challenge (model), which will lead to a special issue of the Journal of Digital Imaging (publication) and interface with standards with an industry advisory panel from SIIM (translation).”

Phase 1, which runs from September 2020 through May 2021, provides nearly $1M to enable rapid development and translation of medical imaging technologies targeting COVID-19 while laying the foundation for advancing Phase 2’s informatics, data science, and integration/validation technologies beyond thoracic radiology. These innovations will catapult research forward by integrating scattered data and models into resources that can be effectively scaled, validated, and translated.

About the Society for Imaging Informatics in Medicine

The Society for Imaging Informatics in Medicine (SIIM) is the leading healthcare professional organization for those interested in the current and future use of informatics in medical imaging. The Society’s mission is to advance medical imaging informatics across the enterprise through education, research, and innovation in a multi-disciplinary community.


Priyanka Harilal

SIIM Director of Marketing 

Publish date

Sep 14, 2020


  • Artificial Intelligence

Media Type

  • Press Release

Audience Type

  • Clinician
  • Developer
  • Imaging IT
  • Researcher/Scientist


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