Artificial intelligence and automation in endoscopy and surgery

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

FPGA-based High-Performance Collision Detection: An Enabling Technique for Image-Guided Robotic Surgery

Collision detection, which refers to the computational problem of finding the relative placement or con-figuration of two or more objects, is an essential component of many applications in computer graphics and robotics. In image-guided robotic surgery, real-time collision detection is critical for preserving healthy anatomical structures during the surgical procedure. However, the computational complexity of the problem usually results in algorithms that operate at low speed. In this paper, we present a fast and accurate algorithm for collision detection between Oriented-Bounding-Boxes (OBBs) that is suitable for real-time implementation. Our proposed Sweep and Prune algorithm can perform a preliminary filtering to reduce the number of objects that need to be tested by the classical Separating Axis Test algorithm, while the OBB pairs of interest are preserved. These OBB pairs are re-checked by the Separating Axis Test algorithm to obtain accurate overlapping status between them. To accelerate the execution, our Sweep and Prune algorithm is tailor-made for the proposed method. Meanwhile, a high performance scalable hardware architecture is proposed by analyzing the intrinsic parallelism of our algorithm, and is implemented on FPGA platform. Results show that our hardware design on the FPGA platform can achieve around 8X higher running speed than the software design on a CPU platform. As a result, the proposed algorithm can achieve a collision frame rate of 1 KHz, and fulfill the requirement for the medical surgery scenario of Robot Assisted Laparoscopy.published_or_final_versio

Clinical applications of robotic technology in vascular and endovascular surgery

BackgroundEmerging robotic technologies are increasingly being used by surgical disciplines to facilitate and improve performance of minimally invasive surgery. Robot-assisted intervention has recently been introduced into the field of vascular surgery to potentially enhance laparoscopic vascular and endovascular capabilities. The objective of this study was to review the current status of clinical robotic applications in vascular surgery.MethodsA systematic literature search was performed in order to identify all published clinical studies related to robotic implementation in vascular intervention. Web-based search engines were searched using the keywords “surgical robotics,” “robotic surgery,” “robotics,” “computer assisted surgery,” and “vascular surgery” or “endovascular” for articles published between January 1990 and November 2009. An evaluation and critical overview of these studies is reported. In addition, an analysis and discussion of supporting evidence for robotic computer-enhanced telemanipulation systems in relation to their applications in laparoscopic vascular and endovascular surgery was undertaken.ResultsSeventeen articles reporting on clinical applications of robotics in laparoscopic vascular and endovascular surgery were detected. They were either case reports or retrospective patient series and prospective studies reporting laparoscopic vascular and endovascular treatments for patients using robotic technology. Minimal comparative clinical evidence to evaluate the advantages of robot-assisted vascular procedures was identified. Robot-assisted laparoscopic aortic procedures have been reported by several studies with satisfactory results. Furthermore, the use of robotic technology as a sole modality for abdominal aortic aneurysm repair and expansion of its applications to splenic and renal artery aneurysm reconstruction have been described. Robotically steerable endovascular catheter systems have potential advantages over conventional catheterization systems. Promising results from applications in cardiac interventions and preclinical studies have urged their use in vascular surgery. Although successful applications in endovascular repair of abdominal aortic aneurysm and lower extremity arterial disease have been reported, published clinical experience with the endovascular robot is limited.ConclusionsRobotic technology may enhance vascular surgical techniques given preclinical evidence and early clinical reports. Further clinical studies are required to quantify its advantages over conventional treatments and define its role in vascular and endovascular surgery