title: Design, implementation and accuracy of a prototype for medical augmented reality.
abstract: OBJECTIVE
  This paper is focused on prototype development and accuracy evaluation of a medical Augmented Reality (AR) system. The accuracy of such a system is of critical importance for medical use, and is hence considered in detail. We analyze the individual error contributions and the system accuracy of the prototype.
  
  
  METHODS
  A passive articulated arm is used to track a calibrated end-effector-mounted video camera. The live video view is superimposed in real time with the synchronized graphical view of CT-derived segmented object(s) of interest within a phantom skull. The AR accuracy mostly depends on the accuracy of the tracking technology, the registration procedure, the camera calibration, and the image scanning device (e.g., a CT or MRI scanner).
  
  
  RESULTS
  The accuracy of the Microscribe arm was measured to be 0.87 mm. After mounting the camera on the tracking device, the AR accuracy was measured to be 2.74 mm on average (standard deviation = 0.81 mm). After using data from a 2-mm-thick CT scan, the AR error remained essentially the same at an average of 2.75 mm (standard deviation = 1.19 mm).
  
  
  CONCLUSIONS
  For neurosurgery, the acceptable error is approximately 2-3 mm, and our prototype approaches these accuracy requirements. The accuracy could be increased with a higher-fidelity tracking system and improved calibration and object registration. The design and methods of this prototype device can be extrapolated to current medical robotics (due to the kinematic similarity) and neuronavigation systems.
authors.affiliation: Electrical and Computer Engineering Department, Wayne State University, Detroit, Michigan 48202, USA. apandya@eng.wayne.edu
authors.forename: Abhilash
authors.initials: A
authors.lastname: Pandya
authors.forename: Mohammad-Reza
authors.initials: MR
authors.lastname: Siadat
authors.forename: Greg
authors.initials: G
authors.lastname: Auner
mesh_terms: D006801:Humans; D007091:Image Processing, Computer-Assisted; D038361:Neuronavigation; D019047:Phantoms, Imaging; D012371:Robotics; D025321:Surgery, Computer-Assisted; D014584:User-Computer Interface