Artificial intelligence and automation in endoscopy and surgery

医学 自动化 人工智能 计算机科学 机械人手术 内窥镜检查 医学物理学 放射科 机械工程 工程类
作者
François Chadebecq,Laurence Lovat,Danail Stoyanov
出处
期刊:Nature Reviews Gastroenterology & Hepatology [Nature Portfolio]
卷期号:20 (3): 171-182 被引量:121
标识
DOI:10.1038/s41575-022-00701-y
摘要

Modern endoscopy relies on digital technology, from high-resolution imaging sensors and displays to electronics connecting configurable illumination and actuation systems for robotic articulation. In addition to enabling more effective diagnostic and therapeutic interventions, the digitization of the procedural toolset enables video data capture of the internal human anatomy at unprecedented levels. Interventional video data encapsulate functional and structural information about a patient’s anatomy as well as events, activity and action logs about the surgical process. This detailed but difficult-to-interpret record from endoscopic procedures can be linked to preoperative and postoperative records or patient imaging information. Rapid advances in artificial intelligence, especially in supervised deep learning, can utilize data from endoscopic procedures to develop systems for assisting procedures leading to computer-assisted interventions that can enable better navigation during procedures, automation of image interpretation and robotically assisted tool manipulation. In this Perspective, we summarize state-of-the-art artificial intelligence for computer-assisted interventions in gastroenterology and surgery. Advances in artificial intelligence (AI) are changing endoscopy and gastrointestinal surgery, including computer-assisted detection and diagnosis, computer-aided navigation, robot-assisted intervention and automated reporting. This Perspective introduces the role of AI in computer-assisted interventions in gastroenterology with insights on regulatory aspects and the challenges ahead.
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