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Communication Dans Un Congrès Année : 2022

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

Résumé

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 realtime 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.
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Dates et versions

hal-03758955 , version 1 (23-08-2022)

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Citer

Karim Botros, Mohammad Alkhatib, David Folio, Antoine Ferreira. Fully Automatic and Real-Time Microrobot Detection and Tracking based on Ultrasound Imaging using Deep Learning. 2022 IEEE International Conference on Robotics and Automation (ICRA), May 2022, Philadelphia, United States. pp.9763-9768, ⟨10.1109/ICRA46639.2022.9812114⟩. ⟨hal-03758955⟩
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