Artificial Intelligence Applications in Interventional Radiology
Carolina Lanza, Salvatore Alessio Angileri, Serena Carriero, Sonia Triggiani, Velio Ascenti, Simone Mortellaro, M Ginolfi, Alessia Leo 等 13 位
Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico University of Milan
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摘要与影响
This review is a brief overview of the current status and the potential role of artificial intelligence (AI) in interventional radiology (IR). The literature published in the last decades was reviewed and the technical developments in terms of radiomics, virtual reality, robotics, fusion imaging, cone-beam computed tomography (CBCT) and Imaging Guidance Software were analyzed. The evidence shows that AI significatively improves pre-procedural planning, intra-procedural navigation, and post-procedural assessment. Radiomics extracts features from optical images of personalized treatment strategies. Virtual reality offers innovative tools especially for training and procedural simulation. Robotic systems, combined with AI, could enhance precision and reproducibility of IR procedures while reducing operator exposure to X-ray. Fusion imaging and CBCT, augmented by AI software, improve real-time guidance and procedural outcomes.
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生物医学Artificial Intelligence in Healthcare and Education
Radiomics and Machine Learning in Medical Imaging · Medical Image Segmentation Techniques
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