A taxonomy of mutual information in medical image registration

Mutual information (MI) is a very important concept in medical image registration for a diagnosis. During the past decade, there have been a large number of studies on multimodal image registration. This extensive attention is due to its high performance in terms of accuracy and robustness. However, there are so many different perspectives on MI that have been discussed and proposed during the last two decades. As a result, it is very difficult to have a holistic view of the field and to select an appropriate method to solve a specific problem in medical image analysis. In order to solve this problem, this paper proposes a novel taxonomy of MI approaches used in medical image registration. In our work, we extensively and comprehensively investigate works proposed in the literature and systematically classify them based on methods of computational processing. Our taxonomy will help to enhance an understanding of various principles of mutual information.