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DOI: 10.14569/IJARAI.2014.030401
PDF

A Registration Method for Multimodal Medical Images Using Contours Mutual Information

Author 1: Ying Qian
Author 2: Meng Li
Author 3: Qingjie Wei
Author 4: Xuemei Ren

International Journal of Advanced Research in Artificial Intelligence(IJARAI), Volume 3 Issue 4, 2014.

  • Abstract and Keywords
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Abstract: In recent years, mutual information has developed as a popular image registration measure especially in multimodality image registration. For different modality medical images, the contour of tissues or organs is similarity. In this paper, an effective new registration method of the multimodal medical images based on the contour mutual information is proposed. Firstly, get the contour through variational level set method. Secondly, within the contour pixels are assigned the same grayscale value, obtain two contour images. Finally, two contour images using mutual information as similarity measure for image registration. The experiment results show that the registration algorithm proposed in this paper can do more effectively and more accurately work than normalized mutual information and gradient mutual information.

Keywords: contour mutual information; mutual information; multimodal medical image; image registration; variational level set method

Ying Qian, Meng Li, Qingjie Wei and Xuemei Ren, “A Registration Method for Multimodal Medical Images Using Contours Mutual Information” International Journal of Advanced Research in Artificial Intelligence(IJARAI), 3(4), 2014. http://dx.doi.org/10.14569/IJARAI.2014.030401

@article{Qian2014,
title = {A Registration Method for Multimodal Medical Images Using Contours Mutual Information},
journal = {International Journal of Advanced Research in Artificial Intelligence},
doi = {10.14569/IJARAI.2014.030401},
url = {http://dx.doi.org/10.14569/IJARAI.2014.030401},
year = {2014},
publisher = {The Science and Information Organization},
volume = {3},
number = {4},
author = {Ying Qian and Meng Li and Qingjie Wei and Xuemei Ren}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

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