Automatic Tool Detection in X-Ray Images for Robotic Assisted Joint Fracture Surgery
- Resource Type
- Conference
- Authors
- Ma, YingLiang; Dagnino, Giulio; Georgilas, Ioannis; Dogramadzi, Sanja
- Source
- 2017 IEEE International Conference on Internet of Things (iThings) and IEEE Green Computing and Communications (GreenCom) and IEEE Cyber, Physical and Social Computing (CPSCom) and IEEE Smart Data (SmartData) ITHINGS-GREENCOM-CPSCOM-SMARTDATA 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. :883-887 Jun, 2017
- Subject
- Communication, Networking and Broadcast Technologies
Computing and Processing
Power, Energy and Industry Applications
Signal Processing and Analysis
Transportation
X-ray imaging
Bones
Tools
Three-dimensional displays
Surgery
Robot kinematics
computer vision
robotics
computer assisted surgery
- Language
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.