Artificial intelligence in the detection of non-biological materials.

Journal: Emergency radiology
Published Date:

Abstract

Artificial Intelligence (AI) has emerged as a transformative force within medical imaging, making significant strides within emergency radiology. Presently, there is a strong reliance on radiologists to accurately diagnose and characterize foreign bodies in a timely fashion, a task that can be readily augmented with AI tools. This article will first explore the most common clinical scenarios involving foreign bodies, such as retained surgical instruments, open and penetrating injuries, catheter and tube malposition, and foreign body ingestion and aspiration. By initially exploring the existing imaging techniques employed for diagnosing these conditions, the potential role of AI in detecting non-biological materials can be better elucidated. Yet, the heterogeneous nature of foreign bodies and limited data availability complicates the development of computer-aided detection models. Despite these challenges, integrating AI can potentially decrease radiologist workload, enhance diagnostic accuracy, and improve patient outcomes.

Authors

  • Liesl Eibschutz
    Department of Radiology Division of Emergency Radiology, Keck School of Medicine, University of Southern California (USC), 1500 San Pablo Street, Los Angeles, CA, 90033, USA.
  • Max Yang Lu
    Department of Radiology Division of Emergency Radiology, Keck School of Medicine, University of Southern California (USC), 1500 San Pablo Street, Los Angeles, CA, 90033, USA.
  • Mashya T Abbassi
    Department of Radiology Division of Emergency Radiology, Keck School of Medicine, University of Southern California (USC), 1500 San Pablo Street, Los Angeles, CA, 90033, USA.
  • Ali Gholamrezanezhad
    Department of Radiology, Keck School of Medicine, University of Southern California (USC), Los Angeles, CA, USA.