Mutual Information: A Similarity Measure for Intensity Based Image Registration

Author(s):  
Hua-mei Chen
2013 ◽  
Vol 433-435 ◽  
pp. 368-371
Author(s):  
Shun Sen Guo ◽  
Yong Xia ◽  
Kuan Quan Wang

Mutual information stems from communication theory, which is commonly used as similarity measure in the field of medical image registration. This approach works directly with image data; no pre-processing or segmentation is required. But calculating the mutual information of images needs a large amount of computation, which in some respect restricts its application. In this paper, by doing some processing on the reference image before the registration, we changed the way of calculating the mutual information to reduce the computation. The result of the experiments shows that the accuracy of registration does not change significantly, whereas the time of calculating the mutual information is decreased significantly.


2001 ◽  
Author(s):  
Kisha Johnson ◽  
Arlene Cole-Rhodes ◽  
Ilya Zavorin ◽  
Jacqueline Le Moigne

Author(s):  
Mohamed E. Khalifa ◽  
Haitham M. Elmessiry ◽  
Khaled M. ElBahnasy ◽  
Hassan M. M. Ramadan

2014 ◽  
Vol 52 (7) ◽  
pp. 4328-4338 ◽  
Author(s):  
Maoguo Gong ◽  
Shengmeng Zhao ◽  
Licheng Jiao ◽  
Dayong Tian ◽  
Shuang Wang

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