Fully Automatic and Real-Time Microrobot Detection and Tracking based on Ultrasound Imaging using Deep Learning

Abstract

Micro-scale robots introduce great prospective into many different medical applications such as targeted drug delivery, minimally invasive surgery and localized bio-metric diagnostics. This research presents a method for object detection and tracking system of a chain-like magnetic microsphere robots using ultrasound imaging in an in-vitro environment. The method estimates the position of the microrobot in real-time using deep learning techniques. The experiments showed that a spherical microrobot with about 500 m in diameter can be detected and tracked in real-time with a high accuracy in dynamic environments. The results exhibit a high detection and tracking accuracy for one, two and three sphere microrobots with the highest accuracy in detection and tracking around 95 % and 93% respectively.