Design and implementation of a real-time research data warehouse: lessons learned from Vanderbilt’s ImageVU (Conference Presentation)

Bennett A. Landman

doi:10.1117/12.2672590

3 April 2023 Design and implementation of a real-time research data warehouse: lessons learned from Vanderbilt’s ImageVU (Conference Presentation)

Bennett A. Landman

Author Affiliations +

Proceedings Volume 12464, Medical Imaging 2023: Image Processing; 124640M (2023) https://doi.org/10.1117/12.2672590
Event: SPIE Medical Imaging, 2023, San Diego, California, United States

Abstract

The field of artificial intelligence in medical imaging is undergoing explosive growth, and Radiology is a prime target for innovation. Research labs and industry innovators are rapidly developing and presenting these methods (e.g., at venues such as SPIE Medical Imaging). Deploying AI tools within a clinical enterprise, even on limited retrospective evaluation, is complicated by security and privacy concerns. Thus, integrating innovations must be weighed against the substantive resources required for local clinical evaluation. To reduce barriers to validation while maintaining rigorous security and privacy standards, Vanderbilt has developed and maintained a research data warehouse for imaging since 2011. Most recently, we integrated an AI Imaging Incubator that serves as a storage destination within a clinical enterprise where images can be directed for novel research evaluation under Institutional Review Board approval. This presentation will discuss our design process and the evolving research pressures that shape our ecosystem.

Conference Presentation

Citation Download Citation

Bennett A. Landman "Design and implementation of a real-time research data warehouse: lessons learned from Vanderbilt’s ImageVU (Conference Presentation)", Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 124640M (3 April 2023); https://doi.org/10.1117/12.2672590

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