Stochastic image registration with user constraints

Ivan Kolesov; Jehoon Lee; Patricio Vela; Allen Tannenbaum

doi:10.1117/12.2007096

13 March 2013 Stochastic image registration with user constraints

Ivan Kolesov, Jehoon Lee, Patricio Vela, Allen Tannenbaum

Proceedings Volume 8669, Medical Imaging 2013: Image Processing; 866933 (2013) https://doi.org/10.1117/12.2007096
Event: SPIE Medical Imaging, 2013, Lake Buena Vista (Orlando Area), Florida, United States

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.

Citation Download Citation

Ivan Kolesov, Jehoon Lee, Patricio Vela, and Allen Tannenbaum "Stochastic image registration with user constraints", Proc. SPIE 8669, Medical Imaging 2013: Image Processing, 866933 (13 March 2013); https://doi.org/10.1117/12.2007096

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