AUTOMATIC TOOL DETECTION IN X-RAY IMAGES FOR ROBOTIC ASSISTED JOINT FRACTURE SURGERY

Ma, YingLiang and Dagnino, Giulio and Georgilas, Ioannis and Dogramadzi, Sanja (2017) AUTOMATIC TOOL DETECTION IN X-RAY IMAGES FOR ROBOTIC ASSISTED JOINT FRACTURE SURGERY. In: The 10th IEEE International Conference on Internet of Things, 21-23 June 2017, Exeter.

[img]
Preview
Text
AUTOMATIC TOOL DETECTION IN X-RAY IMAGES FOR ROBOTIC ASSISTED JOINT FRACTURE SURGERY.pdf

Download (337kB)

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: Conference or Workshop Item (Paper)
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 > UoA11: Computer Science and Informatics
Depositing User: $ Ian McDonald
Date Deposited: 04 Jul 2017 11:45
Last Modified: 04 Jul 2017 11:48
URI: http://www.open-access.bcu.ac.uk/id/eprint/4798

Actions (login required)

View Item View Item

Research

In this section...