Deformable multi-modal image registration by maximizing Rényi's statistical dependence measure

Yunmei Chen; Jiangli Shi; Murali Rao; Jin-Seop Lee

doi:10.3934/ipi.2015.9.79

Article Contents

2015, Volume 9, Issue 1: 79-103. Doi: 10.3934/ipi.2015.9.79

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Deformable multi-modal image registration by maximizing Rényi's statistical dependence measure

1.
Department of Mathematics, 358 Little Hall, PO Box 118105, Gainesville, FL 32611

Received: January 2013

Revised: May 2014

Published: February 2015

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Abstract

A novel variational model for deformable multi-modal image registration is presented in this work. As an alternative to the models based on maximizing mutual information, the Rényi's statistical dependence measure of two random variables is proposed as a measure of the goodness of matching in our objective functional. The proposed model does not require an estimation of the continuous joint probability density function. Instead, it only needs observed independent instances. Moreover, the theory of reproducing kernel Hilbert space is used to simplify the computation. Experimental results and comparisons with several existing methods are provided to show the effectiveness of the model.

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Mathematics Subject Classification: 94A08, 68U10, 65D18.

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