Automatic tool detection in X-Ray images for robotic assisted joint fracture surgery

Ma, YingLiang and Dagnino, Giulio and Georgilas, Ioannis and Dogramadzi, Sanja (2018) Automatic tool detection in X-Ray images for robotic assisted joint fracture surgery. In: Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData), 2017 IEEE International Conference on. IEEE. ISBN 978-1-5386-3066-2

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Abstract

Long-bone fractures such as femur fractures are very
common in trauma centers. Robotic assisted fracture surgery
(RAFS) can facilitate the minimally invasive surgery which reduces scarring, infection risk and long hospital stays. One important step in RAFS is to establish the coordinate system link between patient joint (rigidly connected with the robotic system) and an external tracking system. As X-ray
fluoroscopic images are routinely used during the procedure, an automatic method is proposed to detect and localize
landmarks on the tracking tool using live X-ray image. The proposed method uses combination of block detection,
geometric model matching and principle component
analysis. A successful rate of 91.3% is achieved after testing on 650 X-ray images and accuracy is within 0.5 mm.

Item Type: Book Section
Uncontrolled Keywords: computer vision, robotics, computer assisted surgery
Subjects: B800 Medical Technology
Divisions: Faculty of Computing, Engineering and the Built Environment
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology
Faculty of Computing, Engineering and the Built Environment > School of Computing and Digital Technology > Cyber Security
UoA Collections > REF2021 UoA11: Computer Science and Informatics
Depositing User: Ian Mcdonald
Date Deposited: 04 Jul 2017 11:45
Last Modified: 31 May 2018 15:24
URI: http://www.open-access.bcu.ac.uk/id/eprint/4798

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