title: Landmark-based augmented reality system for paranasal and transnasal endoscopic surgeries.
abstract: BACKGROUND
  In this paper we present a landmark-based augmented reality (AR) endoscope system for endoscopic paranasal and transnasal surgeries along with fast and automatic calibration and registration procedures for the endoscope.
  
  
  METHODS
  Preoperatively the surgeon selects natural landmarks or can define new landmarks in CT volume. These landmarks are overlaid, after proper registration of preoperative CT to the patient, on the endoscopic video stream. The specified name of the landmark, along with selected colour and its distance from the endoscope tip, is also augmented. The endoscope optics are calibrated and registered by fast and automatic methods. Accuracy of the system is evaluated in a metallic grid and cadaver set-up.
  
  
  RESULTS
  Root mean square (RMS) error of the system is 0.8 mm in a controlled laboratory set-up (metallic grid) and was 2.25 mm during cadaver studies.
  
  
  CONCLUSIONS
  A novel landmark-based AR endoscope system is implemented and its accuracy is evaluated. Augmented landmarks will help the surgeon to orientate and navigate the surgical field. Studies prove the capability of the system for the proposed application. Further clinical studies are planned in near future.
authors.affiliation: ARTORG Research Centre, University of Bern, Stauffacherstrasse 78, Bern, Switzerland. rameshtu@yahoo.com
authors.forename: Ramesh
authors.initials: R
authors.lastname: Thoranaghatte
authors.forename: Jaime
authors.initials: J
authors.lastname: Garcia
authors.forename: Marco
authors.initials: M
authors.lastname: Caversaccio
authors.forename: Daniel
authors.initials: D
authors.lastname: Widmer
authors.forename: Miguel A
authors.initials: MA
authors.lastname: Gonzalez Ballester
authors.forename: Lutz-P
authors.initials: LP
authors.lastname: Nolte
authors.forename: Guoyan
authors.initials: G
authors.lastname: Zheng
mesh_terms: D002102:Cadaver; D019723:Endoscopes; D004724:Endoscopy / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000295:instrumentation / Q000379:methods; D010256:Paranasal Sinuses / Q000000981:diagnostic imaging / Q000473:pathology / Q000601:surgery*; D015203:Reproducibility of Results; D012371:Robotics / Q000295:instrumentation* / Q000379:methods; D012680:Sensitivity and Specificity; D019291:Skull Base / Q000000981:diagnostic imaging / Q000473:pathology / Q000601:surgery*; D025321:Surgery, Computer-Assisted / Q000295:instrumentation* / Q000379:methods; D014057:Tomography, X-Ray Computed / Q000295:instrumentation* / Q000379:methods; D014584:User-Computer Interface