Radiologic Artifacts: Recognition, Minimisation, and Clinical Implications
Abstract
Artifacts in radiologic imaging, including CT and MRI, pose significant challenges to diagnostic precision by obscuring or distorting anatomical structures. This review examines major artifact types, such as metal, bone, motion, and beam-hardening artifacts, and discusses the effectiveness of current minimization strategies, including dual-energy CT, iterative reconstruction, and AI-driven models. Key findings suggest that while advanced techniques have improved artifact management, certain artifacts, particularly those caused by metallic implants, continue to compromise image quality. The review underscores the clinical implications of artifacts, which may lead to diagnostic inaccuracies, and calls for ongoing research into advanced correction techniques. By refining artifact reduction technologies, future advancements can help mitigate diagnostic risks, ensuring clearer and more accurate imaging.
Copyright (c) 2024 Sorin-Marian Mârza, Radu Lăcătuș, Felix Daniel Lucaci, Robert Cristian Purdoiu

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