{"title":"The Role and Future of Artificial Intelligence in Robotic Image-Guided Interventions.","authors":"Tom Boeken, Hwa-Pyung David Lim, Emil I Cohen","doi":"10.1016/j.tvir.2024.101001","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence and robotics are transforming interventional radiology, driven by advancements in computer vision, robotics and procedural automation. Historically focused on diagnostics, AI now also enhances procedural capabilities in IR, enabling future robotic systems to handle complex tasks such as catheter manipulation or needle placement with increasing precision and reliability. Early robotic systems in IR demonstrated improved accuracy in both vascular and percutaneous interventions, though none were equipped with automatic decision-making. This review tends to show the potential in improving procedural outcomes with AI for robotics, though challenges remain. Techniques like reinforcement learning and haptic vision are under investigation to address several issues, training robots to adapt based on real-time feedback from the environment. As AI-driven robotics evolve, IR could shift towards a model where human expertise oversees the technology rather than performs the intervention itself.</p>","PeriodicalId":51613,"journal":{"name":"Techniques in Vascular and Interventional Radiology","volume":"27 4","pages":"101001"},"PeriodicalIF":1.4000,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Techniques in Vascular and Interventional Radiology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1016/j.tvir.2024.101001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/11/28 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"RADIOLOGY, NUCLEAR MEDICINE & MEDICAL IMAGING","Score":null,"Total":0}
引用次数: 0
Abstract
Artificial intelligence and robotics are transforming interventional radiology, driven by advancements in computer vision, robotics and procedural automation. Historically focused on diagnostics, AI now also enhances procedural capabilities in IR, enabling future robotic systems to handle complex tasks such as catheter manipulation or needle placement with increasing precision and reliability. Early robotic systems in IR demonstrated improved accuracy in both vascular and percutaneous interventions, though none were equipped with automatic decision-making. This review tends to show the potential in improving procedural outcomes with AI for robotics, though challenges remain. Techniques like reinforcement learning and haptic vision are under investigation to address several issues, training robots to adapt based on real-time feedback from the environment. As AI-driven robotics evolve, IR could shift towards a model where human expertise oversees the technology rather than performs the intervention itself.
期刊介绍:
Interventional radiology is an area of clinical diagnosis and management that is highly technique-oriented. Therefore, the format of this quarterly journal, which combines the visual impact of an atlas with the currency of a journal, lends itself perfectly to presenting the topics. Each issue is guest edited by a leader in the field and is focused on a single clinical technique or problem. The presentation is enhanced by superb illustrations and descriptive narrative outlining the steps of a particular procedure. Interventional radiologists, neuroradiologists, vascular surgeons and neurosurgeons will find this a useful addition to the clinical literature.