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Optimization Methods for Medical Images Registration based on Intensity  

Lee, Myung-Eun (Department of Computer Science, Chonnam National University)
Kim, Soo-Hyung (Department of Computer Science, Chonnam National University)
Lim, Jun-Sik (Department of Computer Science, Chonnam National University)
Publication Information
Journal of the Institute of Electronics Engineers of Korea CI / v.46, no.6, 2009 , pp. 1-6 More about this Journal
Abstract
We propose an intensity-based image registration method for medical images. The proposed registration is performed by the use of a new measure based on the entropy of conditional probabilities. To achieve the registration, we define a modified conditional entropy (MCE) computed from the joint histograms for the area intensities of two given images. And we conduct experiments with our method as well as existing methods based on the sum of squared differences (SSD), normalized correlation coefficient (NCC), normalized mutual information (NMI) criteria. We evaluate the precision of SSD-, NCC-, MI- and MCE-based measurements by comparing the registration obtained from the same modality magnetic resonance (MR) images and the different modality transformed MR/transformed CT images. The experimental results show that the proposed method is faster and more accurate than other optimization methods.
Keywords
Medical Image Registration; Conditional Entropy; Mutual Information; MR; CT;
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