Ultrasound-guided robotic navigation with deep reinforcement learning
Hase H, Azampour MF, Tirindelli M, Paschali M, Simson W, Fatemizadeh E, Navab N (2020)
Publication Type: Conference contribution
Publication year: 2020
Journal
Publisher: Institute of Electrical and Electronics Engineers Inc.
Pages Range: 5534-5541
Conference Proceedings Title: IEEE International Conference on Intelligent Robots and Systems
Event location: Las Vegas, NV, USA
ISBN: 9781728162126
DOI: 10.1109/IROS45743.2020.9340913
Abstract
In this paper we introduce the first reinforcement learning (RL) based robotic navigation method which utilizes ultrasound (US) images as an input. Our approach combines state-of-the-art RL techniques, specifically deep Q-networks (DQN) with memory buffers and a binary classifier for deciding when to terminate the task.Our method is trained and evaluated on an in-house collected data-set of 34 volunteers and when compared to pure RL and supervised learning (SL) techniques, it performs substantially better, which highlights the suitability of RL navigation for US-guided procedures. When testing our proposed model, we obtained a 82.91% chance of navigating correctly to the sacrum from 165 different starting positions on 5 different unseen simulated environments.
Involved external institutions
Technische Universität München (TUM)
Germany (DE)
Sharif University of Technology / دانشگاه صنعتی شریف (SUT)
Iran, Islamic Republic of (IR)
Germany (DE)
Sharif University of Technology / دانشگاه صنعتی شریف (SUT)
Iran, Islamic Republic of (IR)
How to cite
APA:
Hase, H., Azampour, M.F., Tirindelli, M., Paschali, M., Simson, W., Fatemizadeh, E., & Navab, N. (2020). Ultrasound-guided robotic navigation with deep reinforcement learning. In IEEE International Conference on Intelligent Robots and Systems (pp. 5534-5541). Las Vegas, NV, USA: Institute of Electrical and Electronics Engineers Inc..
MLA:
Hase, Hannes, et al. "Ultrasound-guided robotic navigation with deep reinforcement learning." Proceedings of the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2020, Las Vegas, NV, USA Institute of Electrical and Electronics Engineers Inc., 2020. 5534-5541.
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