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Proceedings Paper

Comparison and evaluation of joint histogram estimation methods for mutual information based image registration
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Paper Abstract

Joint histogram is the only quantity required to calculate the mutual information (MI) between two images. For MI based image registration, joint histograms are often estimated through linear interpolation or partial volume interpolation (PVI). It has been pointed out that both methods may result in a phenomenon known as interpolation induced artifacts. In this paper, we implemented a wide range of interpolation/approximation kernels for joint histogram estimation. Some kernels are nonnegative. In this case, these kernels are applied in two ways as the linear kernel is applied in linear interpolation and PVI. In addition, we implemented two other joint histogram estimation methods devised to overcome the interpolation artifact problem. They are nearest neighbor interpolation with jittered sampling with/without histogram blurring and data resampling. We used the clinical data obtained from Vanderbilt University for all of the experiments. The objective of this study is to perform a comprehensive comparison and evaluation of different joint histogram estimation methods for MI based image registration in terms of artifacts reduction and registration accuracy.

Paper Details

Date Published: 29 April 2005
PDF: 12 pages
Proc. SPIE 5747, Medical Imaging 2005: Image Processing, (29 April 2005); doi: 10.1117/12.596417
Show Author Affiliations
Yongfang Liang, Univ. of Texas at Arlington (United States)
Hua-mei Chen, Univ. of Texas at Arlington (United States)

Published in SPIE Proceedings Vol. 5747:
Medical Imaging 2005: Image Processing
J. Michael Fitzpatrick; Joseph M. Reinhardt, Editor(s)

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