title: Unobtrusive augmentation of critical hidden structures in laparoscopy.
abstract: A fundamental problem in implementing augmented reality (AR) surgery is characterizing how visualizations effect surgeon perception. This problem is important because procedure outcomes depend on surgeon ability to perceive hidden and visible structure interrelation which may be quite dynamic. AR techniques such as x-ray vision are designed to compensate for or reintroduce depth cues lost overlaying hidden structures on a view stream. Such enhancements are necessarily deviations, which may obtrude. This paper provides discussion of hidden structure rendering, analysis, a proposed framework, protocol and experiment (n=2500) for safe evaluation within in vitro laparoscopic video from, and minimal transfer to, in vivo surgery. Results evidence our protocol enables comparison of hidden structure visualizations on task efficacy in vitro and suggest promising new direction towards validating AR in live surgery.
authors.affiliation: Robot Perception and Action Lab (RPAL), University of South Florida, Tampa, FL.
authors.forename: Adrian S
authors.initials: AS
authors.lastname: Johnson
authors.affiliation: Center for Advanced Medical Learning and Simulation (CAMLS), Department of Surgery, University of South Florida, Tampa FL, USA.
authors.forename: Jaime
authors.initials: J
authors.lastname: Sanchez
authors.affiliation: Robot Perception and Action Lab (RPAL), University of South Florida, Tampa, FL.
authors.forename: Alexander
authors.initials: A
authors.lastname: French
authors.affiliation: Robot Perception and Action Lab (RPAL), University of South Florida, Tampa, FL.
authors.forename: Yu
authors.initials: Y
authors.lastname: Sun
mesh_terms: D000715:Anatomy; D003867:Depth Perception; D006801:Humans; D007091:Image Processing, Computer-Assisted; D010535:Laparoscopy / Q000379:methods*; D025321:Surgery, Computer-Assisted; D014584:User-Computer Interface