Using registration uncertainty visualization in a user study of a simple surgical task.
We present a novel method to visualize registration uncertainty and a simple study to motivate the use of uncertainty visualization in computer-assisted surgery. Our visualization method resulted in a statistically significant reduction in the number of attempts required to localize a target, and a statistically significant reduction in the number of targets that our subjects failed to localize. Most notably, our work addresses the existence of uncertainty in guidance and offers a first step towards helping surgeons make informed decisions in the presence of imperfect data.
Simpson
Amber L
AL
School of Computing, Queen's University, Kingston, Canada. simpson@cs.queensu.ca
Ma
Burton
B
Chen
Elvis C S
EC
Ellis
Randy E
RE
Stewart
A James
AJ
D000465:Algorithms; D003198:Computer Simulation; D005266:Femoral Neoplasms / Q000000981:diagnostic imaging* / Q000601:surgery*; D006801:Humans; D008954:Models, Biological; D015233:Models, Statistical; D010017:Osteoma, Osteoid / Q000000981:diagnostic imaging* / Q000601:surgery*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D025321:Surgery, Computer-Assisted / Q000379:methods*; D013647:Task Performance and Analysis; D014057:Tomography, X-Ray Computed / Q000379:methods; D014584:User-Computer Interface