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Proceedings Paper

Stochastic image registration with user constraints
Author(s): Ivan Kolesov; Jehoon Lee; Patricio Vela; Allen Tannenbaum
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Paper Abstract

Constrained registration is an active area of research and is the focus of this work. This note describes a non-rigid image registration framework for incorporating landmark constraints. Points that must remain stationary are selected, the user chooses the spatial extent of the inputs, and an automatic step computes the deformable registration, respecting the constraints. Parametrization of the deformation field is 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. This approach is based on the particle filter for performing constrained optimization; it explores a series of states defining a deformation field that is physically meaningful (i.e., invertible) and prevents chosen points from moving. Results on synthetic two dimensional images are presented.

Paper Details

Date Published: 13 March 2013
PDF: 7 pages
Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 866933 (13 March 2013); doi: 10.1117/12.2007096
Show Author Affiliations
Ivan Kolesov, Georgia Institute of Technology (United States)
Comprehensive Cancer Ctr., Univ. of Alabama at Birmingham (United States)
Jehoon Lee, Comprehensive Cancer Ctr., Univ. of Alabama at Birmingham (United States)
Patricio Vela, Georgia Institute of Technology (United States)
Allen Tannenbaum, Comprehensive Cancer Ctr., Univ. of Alabama at Birmingham (United States)

Published in SPIE Proceedings Vol. 8669:
Medical Imaging 2013: Image Processing
Sebastien Ourselin; David R. Haynor, Editor(s)

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