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

Ma, YingLiang ORCID: https://orcid.org/0000-0001-5770-5843, Dagnino, Giulio, Georgilas, Ioannis and Dogramadzi, Sanja (2018) Automatic tool detection in X-ray images for robotic assisted joint fracture surgery. In: Proceedings - 2017 IEEE International Conference on Internet of Things, IEEE Green Computing and Communications, IEEE Cyber, Physical and Social Computing, IEEE Smart Data, iThings-GreenCom-CPSCom-SmartData 2017. The Institute of Electrical and Electronics Engineers (IEEE), pp. 883-887.

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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
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 06 Jan 2023 11:31
Last Modified: 06 Jan 2023 11:31
URI: https://ueaeprints.uea.ac.uk/id/eprint/90441
DOI: 10.1109/iThings-GreenCom-CPSCom-SmartData.2017.136

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