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International Journal of Biomedical Imaging
Volume 2007 (2007), Article ID 93479, 10 pages
http://dx.doi.org/10.1155/2007/93479
Research Article

Registration of Brain MRI/PET Images Based on Adaptive Combination of Intensity and Gradient Field Mutual Information

1Medical Image Processing Group, Key Laboratory of Complex Systems and Intelligence Science, Institute of Automation, Chinese Academy of Science, P.O. Box 2728, Beijing 100080, China
2Life Science Center, Xidian University, Xi'an, Shaanxi 710071, China

Received 10 May 2006; Revised 13 January 2007; Accepted 22 January 2007

Academic Editor: Robert R. Edelman

Copyright © 2007 Jiangang Liu and Jie Tian. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

Traditional mutual information (MI) function aligns two multimodality images with intensity information, lacking spatial information, so that it usually presents many local maxima that can lead to inaccurate registration. Our paper proposes an algorithm of adaptive combination of intensity and gradient field mutual information (ACMI). Gradient code maps (GCM) are constructed by coding gradient field information of corresponding original images. The gradient field MI, calculated from GCMs, can provide complementary properties to intensity MI. ACMI combines intensity MI and gradient field MI with a nonlinear weight function, which can automatically adjust the proportion between two types MI in combination to improve registration. Experimental results demonstrate that ACMI outperforms the traditional MI and it is much less sensitive to reduced resolution or overlap of images.