Robotic Intra-Operative Ultrasound: Virtual Environments and Parallel Systems

Robotic intra-operative ultrasound has the potential to improve the conventional practice of diagnosis and procedure guidance that are currently performed manually. Working towards automatic or semi-automatic ultrasound, being able to define ultrasound views and the corresponding probe poses via intelligent approaches become crucial. Based on the concept of parallel system which incorporates the ingredients of artificial systems, computational experiments, and parallel execution, this paper utilized a recent developed robotic trans-esophageal ultrasound system as the study object to explore the method for developing the corresponding virtual environments and present the potential applications of such systems. The proposed virtual system includes the use of 3D slicer as the main workspace and graphic user interface (GUI), Matlab engine to provide robotic control algorithms and customized functions, and PLUS (Public software Library for UltraSound imaging research) toolkit to generate simulated ultrasound images. Detailed implementation methods were presented and the proposed features of the system were explained. Based on this virtual system, example uses and case studies were presented to demonstrate its capabilities when used together with the physical TEE robot. This includes standard view definition and customized view optimization for pre-planning and navigation, as well as robotic control algorithm evaluations to facilitate real-time automatic probe pose adjustments. To conclude, the proposed virtual system would be a powerful tool to facilitate the further developments and clinical uses of the robotic intra-operative ultrasound systems.

Automated summary

This research explores the development of virtual environments using a robotic trans-esophageal ultrasound system, utilizing 3D slicer as the main workspace and GUI, Matlab engine for control algorithms, and PLUS toolkit for simulated ultrasound images. Detailed implementation methods and system features were presented, along with case studies demonstrating its capabilities when used together with the physical TEE robot.