@inproceedings{2caf820a50634f5c97f661c77b7ef9d5,
title = "Rendering-based video-CT registration with physical constraints for image-guided endoscopic sinus surgery",
abstract = "We present a system for registering the coordinate frame of an endoscope to pre- or intra-operatively acquired CT data based on optimizing the similarity metric between an endoscopic image and an image predicted via rendering of CT. Our method is robust and semi-automatic because it takes account of physical constraints, specifically, collisions between the endoscope and the anatomy, to initialize and constrain the search. The proposed optimization method is based on a stochastic optimization algorithm that evaluates a large number of similarity metric functions in parallel on a graphics processing unit. Images from a cadaver and a patient were used for evaluation. The registration error was 0.83 mm and 1.97 mm for cadaver and patient images respectively. The average registration time for 60 trials was 4.4 seconds. The patient study demonstrated robustness of the proposed algorithm against a moderate anatomical deformation.",
keywords = "Endoscopic sinus surgery, Image-guided endoscopic surgery, Rendering-based video-CT registration",
author = "Y. Otake and S. Leonard and A. Reiter and P. Rajan and Siewerdsen, {J. H.} and M. Ishii and Taylor, {R. H.} and Hager, {G. D.}",
note = "Publisher Copyright: {\textcopyright} 2015 SPIE.; Medical Imaging 2015: Image-Guided Procedures, Robotic Interventions, and Modeling ; Conference date: 22-02-2015 Through 24-02-2015",
year = "2015",
doi = "10.1117/12.2081732",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Webster, {Robert J.} and Yaniv, {Ziv R.}",
booktitle = "Medical Imaging 2015",
}