CVApr 29, 2024

VISION: Toward a Standardized Process for Radiology Image Management at the National Level

arXiv:2404.18842v13 citationsh-index: 49International Journal of Media and Networks
Originality Synthesis-oriented
AI Analysis

This addresses the problem of standardizing radiology image management for medical researchers, but it is incremental as it focuses on specific experiences and challenges rather than a novel solution.

The paper tackles the challenge of compiling and analyzing radiological images for research by describing experiences in establishing a trusted collection linked to the VA electronic health record database, resulting in insights into procedures for transferring images and identifying roadblocks for automation.

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 and bottlenecks in this process that may hinder future efforts at automation.

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