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Proceedings Paper

Constructing spherical panoramas of a bladder phantom from endoscopic video using bundle adjustment
Author(s): Timothy D. Soper; John E. Chandler; Michael P. Porter; Eric J. Seibel
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Paper Abstract

The high recurrence rate of bladder cancer requires patients to undergo frequent surveillance screenings over their lifetime following initial diagnosis and resection. Our laboratory is developing panoramic stitching software that would compile several minutes of cystoscopic video into a single panoramic image, covering the entire bladder, for review by an urolgist at a later time or remote location. Global alignment of video frames is achieved by using a bundle adjuster that simultaneously recovers both the 3D structure of the bladder as well as the scope motion using only the video frames as input. The result of the algorithm is a complete 360° spherical panorama of the outer surface. The details of the software algorithms are presented here along with results from both a virtual cystoscopy as well from real endoscopic imaging of a bladder phantom. The software successfully stitched several hundred video frames into a single panoramic with subpixel accuracy and with no knowledge of the intrinsic camera properties, such as focal length and radial distortion. In the discussion, we outline future work in development of the software as well as identifying factors pertinent to clinical translation of this technology.

Paper Details

Date Published: 1 March 2011
PDF: 12 pages
Proc. SPIE 7964, Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling, 796417 (1 March 2011); doi: 10.1117/12.878299
Show Author Affiliations
Timothy D. Soper, Univ. of Washington (United States)
John E. Chandler, Univ. of Washington (United States)
Michael P. Porter, Univ. of Washington (United States)
Eric J. Seibel, Univ. of Washington (United States)

Published in SPIE Proceedings Vol. 7964:
Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling
Kenneth H. Wong; David R. Holmes III, Editor(s)

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