Share Email Print

Proceedings Paper

A statistical similarity measure for non-rigid multi-modal image registration
Author(s): Jiangli Shi; Yunmei Chen; Murali Rao; Jinseop Lee
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

We present a novel variational framework for deformable multi-modal image registration. Our approach is based on Renyi's statistical dependence measure of two random variables with the use of reproducing kernel Hilbert spaces associated with Gaussian kernels to simplify the computation. The popularly used method of maximizing mutual information based optimization algorithms are complex and sensitive to the quantization of the intensities, because it requires the estimation of continuous joint probability density function (pdf). The proposed model does not deal with joint pdf but instead observed independent samples. Experimental results are provided to show the effectiveness of the model.

Paper Details

Date Published: 12 March 2010
PDF: 12 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 762307 (12 March 2010); doi: 10.1117/12.844553
Show Author Affiliations
Jiangli Shi, Univ. of Florida (United States)
Yunmei Chen, Univ. of Florida (United States)
Murali Rao, Univ. of Florida (United States)
Jinseop Lee, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

© SPIE. Terms of Use
Back to Top