4.7 Article

Mutual information-based multimodal image registration using a novel joint histogram estimation

期刊

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
卷 32, 期 3, 页码 202-209

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PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2007.12.001

关键词

mutual information; local extreme; joint histogram estimation; Hanning windowed sine; rigid and non-rigid registration

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Mutual information (MI)-based image registration has been proved to be very effective in multimodal medical image applications. For computing the mutual information between two images, the joint histogram needs to be estimated. As we know, the joint histogram estimation through linear interpolation and partial volume (PV) interpolation methods may result in the emergency of the local extreme in mutual information registration function. The local extreme is likely to hamper the optimization process and influence the registration accuracy. In this paper, we present a novel joint histogram estimation method (HPV) by using an approximate function of Harming windowed sine as kernel function of partial volume interpolation. We apply it to both rigid registration and non-rigid registration. In addition, we give a new method estimating the gradient of mutual information with respect to the model parameters during non-rigid registration. By the experiments on both synthetic and real images, it is clearly shown that the new algorithm has the ability to reduce the local extreme, and the registration accuracy is improved. (C) 2007 Elsevier Ltd. All rights reserved.

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