Image Quality in the Era of Artificial Intelligence
Jana G. Delfino, Jason L. Granstedt, Frank W. Samuelson, Robert Ochs, and Krishna Juluru

TL;DR
AI enhances radiological images by improving clarity and speed but introduces new failure modes, making understanding its limitations essential for safe application.
Contribution
This paper highlights the limitations and potential risks of AI-driven image reconstruction and enhancement in radiology, promoting safer use of the technology.
Findings
AI improves image sharpness and acquisition speed
AI can introduce new failure modes
Understanding limitations is crucial for safe AI use
Abstract
Artificial intelligence (AI) is being deployed within radiology at a rapid pace. AI has proven an excellent tool for reconstructing and enhancing images that appear sharper, smoother, and more detailed, can be acquired more quickly, and allowing clinicians to review them more rapidly. However, incorporation of AI also introduces new failure modes and can exacerbate the disconnect between perceived quality of an image and information content of that image. Understanding the limitations of AI-enabled image reconstruction and enhancement is critical for safe and effective use of the technology. Hence, the purpose of this communication is to bring awareness to limitations when AI is used to reconstruct or enhance a radiological image, with the goal of enabling users to reap benefits of the technology while minimizing risks.
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Taxonomy
TopicsArtificial Intelligence in Healthcare and Education · Radiology practices and education · Digital Radiography and Breast Imaging
