Marahrens, N., Jones, D., Stevenson, J. et al. (4 more authors) (2024) Enabling Autonomous Ultrasound-Guided Tumor Ablation During Robotic Surgery. In: 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob). 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), 01-04 Sep 2024, Heidelberg, Germany. IEEE , pp. 1516-1522. ISBN 979-8-3503-8653-0
Abstract
While technologies such as cryo- or radio-frequency ablation allow for less invasive treatment of tumors than re-section, they still require needles to reach the target location with the potential risk of spreading tumor tissue around. High Intensity Focused Ultrasound (HIFU) on the other hand allows for a completely remote and concentrated delivery of energy to a target location without the need for direct access and is particularly well suited to be robotically guided and thus used as part of an autonomous system. While robotic HIFU devices have been extensively explored for extracorporeal applications, their application into a laparoscopic setting is still widely unexplored. This paper presents a novel robotic HIFU pick-up device along with an automated workflow that includes the autonomous acquisition of the tumor geometry via Ultrasound (US) imaging, trajectory planning and autonomous execution of the HIFU ablation constraint by the tissue surface. Therefore, a novel sensorised water-filled membrane is developed and evaluated, enabling hybrid force position control that allows for minimising interaction forces with the tissue surface while maintaining sufficient acoustic coupling for ablation. Experiments on a phantom with a HIFU probe dummy demonstrate the effectiveness of the approach in targeting hidden structures.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2024 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Electronic & Electrical Engineering (Leeds) > Robotics, Autonomous Systems & Sensing (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Dec 2024 11:55 |
Last Modified: | 19 Dec 2024 11:55 |
Published Version: | https://ieeexplore.ieee.org/document/10719947 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/biorob60516.2024.10719947 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:221008 |