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Proceedings Paper

Uniscale multi-view registration using double dog-leg method
Author(s): Chao-I Chen; Dusty Sargent; Chang-Ming Tsai; Yuan-Fang Wang; Dan Koppel
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Paper Abstract

3D computer models of body anatomy can have many uses in medical research and clinical practices. This paper describes a robust method that uses videos of body anatomy to construct multiple, partial 3D structures and then fuse them to form a larger, more complete computer model using the structure-from-motion framework. We employ the Double Dog-Leg (DDL) method, a trust-region based nonlinear optimization method, to jointly optimize the camera motion parameters (rotation and translation) and determine a global scale that all partial 3D structures should agree upon. These optimized motion parameters are used for constructing local structures, and the global scale is essential for multi-view registration after all these partial structures are built. In order to provide a good initial guess of the camera movement parameters and outlier free 2D point correspondences for DDL, we also propose a two-stage scheme where multi-RANSAC with a normalized eight-point algorithm is first performed and then a few iterations of an over-determined five-point algorithm is used to polish the results. Our experimental results using colonoscopy video show that the proposed scheme always produces more accurate outputs than the standard RANSAC scheme. Furthermore, since we have obtained many reliable point correspondences, time-consuming and error-prone registration methods like the iterative closest points (ICP) based algorithms can be replaced by a simple rigid-body transformation solver when merging partial structures into a larger model.

Paper Details

Date Published: 13 March 2009
PDF: 10 pages
Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72611F (13 March 2009); doi: 10.1117/12.810966
Show Author Affiliations
Chao-I Chen, Univ. of California, Santa Barbara (United States)
Dusty Sargent, STI Medical Systems (United States)
Chang-Ming Tsai, Univ. of California, Santa Barbara (United States)
Yuan-Fang Wang, Univ. of California, Santa Barbara (United States)
Dan Koppel, STI Medical Systems (United States)

Published in SPIE Proceedings Vol. 7261:
Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling
Michael I. Miga; Kenneth H. Wong, Editor(s)

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