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

Karim Botross; Alkhatib, Mohammad; David Folio; Antoine Ferreira

doi:10.1109/ICRA46639.2022.9812114

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 realtime using deep learning techniques. The experiments showed that a spherical microrobot with about 500µm 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.

Keywords: Deep learning, Ultrasonic imaging, Targeted drug delivery, Target tracking, Navigation, Perturbation methods, Object detection

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Funding

This work was supported by the Region Centre Val de Loire Fund with the BUBBLEBOT project.

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Citation

BibTeX citation:

@inproceedings{botross2022,
  author = {Botross, Karim and Mohammad , Alkhatib and Folio, David and
    Ferreira, Antoine},
  publisher = {IEEE},
  title = {Fully {Automatic} and {Real-Time} {Microrobot} {Detection}
    and {Tracking} Based on {Ultrasound} {Imaging} Using {Deep}
    {Learning}},
  booktitle = {IEEE Conference on Robotics and Automation (ICRA)},
  date = {2022-07-12},
  eventdate = {2022/05/2022-23/05/27},
  url = {https://dfolio.fr/publications/conferences/2022botrosICRA.html},
  doi = {10.1109/ICRA46639.2022.9812114},
  langid = {en-US},
  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 realtime using deep learning
    techniques. The experiments showed that a spherical microrobot with
    about 500µm 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.}
}

For attribution, please cite this work as:

Botross K., Mohammad A., Folio D., and Ferreira A., “Fully Automatic and Real-Time Microrobot Detection and Tracking based on Ultrasound Imaging using Deep Learning,” in IEEE Conference on Robotics and Automation (ICRA), Philadelphia, United States, 2022 [Online]. Available: https://dfolio.fr/publications/conferences/2022botrosICRA.html