VISION: Toward a Standardized Process for Radiology Image Management at the National Level
Kathryn Knight, Ioana Danciu, Olga Ovchinnikova, Jacob Hinkle, Mayanka, Chandra Shekar, Debangshu Mukherjee, Eileen McAllister, Caitlin Rizy, Kelly, Cho, Amy C. Justice, Joseph Erdos, Peter Kuzmak, Lauren Costa, Yuk-Lam Ho,, Reddy Madipadga, Suzanne Tamang, Ian Goethert

TL;DR
This paper discusses the challenges and procedures involved in creating a standardized, research-ready radiology image repository linked to a large healthcare database, highlighting bottlenecks and insights for automation.
Contribution
It provides a detailed account of establishing a trusted, research-ready radiology image collection linked to the VA database, including procedures and challenges encountered.
Findings
Identified key procedures for transferring images from clinical to research environments.
Highlighted bottlenecks hindering automation in image collection.
Provided insights for future standardization and automation efforts.
Abstract
The compilation and analysis of radiological images poses numerous challenges for researchers. The sheer volume of data as well as the computational needs of algorithms capable of operating on images are extensive. Additionally, the assembly of these images alone is difficult, as these exams may differ widely in terms of clinical context, structured annotation available for model training, modality, and patient identifiers. In this paper, we describe our experiences and challenges in establishing a trusted collection of radiology images linked to the United States Department of Veterans Affairs (VA) electronic health record database. We also discuss implications in making this repository research-ready for medical investigators. Key insights include uncovering the specific procedures required for transferring images from a clinical to a research-ready environment, as well as roadblocks…
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Taxonomy
TopicsRadiology practices and education · Radiation Dose and Imaging · Advanced X-ray and CT Imaging
