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12 March 2010Medical image registration using the modified conditional entropy measure combining the spatial and intensity information
We propose an image registration technique using spatial and intensity information. The registration is conducted by the
use of a measure based on the entropy of conditional probabilities. To achieve the registration, we first define a modified
conditional entropy (MCE) computed from the joint histograms for the area intensities of two given images. In order to
combine the spatial information into a traditional registration measure, we use the gradient vector flow field. Then the
MCE is computed from the gradient vector flow intensity (GVFI) combining the gradient information and their intensity
values of original images. To evaluate the performance of the proposed registration method, we conduct various
experiments with our method as well as existing method based on the mutual information (MI) criteria. We evaluate the
precision of MI- and MCE-based measurements by comparing the registration obtained from MR images and
transformed CT images. The experimental results show that our proposed method is a more accurate technique.
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Myung-Eun Lee, Soo-hyung Kim, Wan-Hyun Cho, Sun-Worl Kim, Jong-Hyun Park, Soon-Young Park, Jun-Sik Lim, "Medical image registration using the modified conditional entropy measure combining the spatial and intensity information," Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76233A (12 March 2010); https://doi.org/10.1117/12.844601