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Proceedings Paper

A stochastic approach for non-rigid image registration
Author(s): Ivan Kolesov; Jehoon Lee; Patricio Vela; Allen Tannenbaum
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Paper Abstract

This note describes a non-rigid image registration approach that parametrizes the deformation field by an additive composition of a similarity transformation and a set of Gaussian radial basis functions. The bases’ centers, variances, and weights are determined with a global optimization approach that is introduced in this work. This approach consists of simulated annealing with a particle filter based generator function to perform the optimization. Additionally, a local refinement is performed to capture the remaining misalignment. The deformation is constrained to be physically meaningful (i.e., invertible). Results on 2D and 3D data sets demonstrate the algorithm’s robustness to large deformations.

Paper Details

Date Published: 19 February 2013
PDF: 15 pages
Proc. SPIE 8655, Image Processing: Algorithms and Systems XI, 86550U (19 February 2013); doi: 10.1117/12.2004400
Show Author Affiliations
Ivan Kolesov, Georgia Institute of Technology (United States)
The Univ. of Alabama at Birmingham (United States)
Jehoon Lee, The Univ. of Alabama at Birmingham (United States)
Patricio Vela, Georgia Institute of Technology (United States)
Allen Tannenbaum, The Univ. of Alabama at Birmingham (United States)


Published in SPIE Proceedings Vol. 8655:
Image Processing: Algorithms and Systems XI
Karen O. Egiazarian; Sos S. Agaian; Atanas P. Gotchev, Editor(s)

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