A survey on mutual information based medical image registration algorithms

The process of aligning one image, in the coordinate system of another is called registration. Image registration is vital in the medical domain and is used for diagnosis, therapy planning, and treatment of diseases. Due to its huge applicability and importance, medical image registration has emerged to be a separate domain of research. Beginning from the invasive landmark based registration, innumerable algorithms have been proposed to register two images of the human physiology. However, a breakthrough in the literature occurred when an information theory based measure, mutual information was used to register two images. Since then a large number of new algorithms have developed, which use mutual information for fully automatic registration of medical images. This paper is a survey of these algorithms. Beginning from its development, it discusses about some of the major works done on mutual information based image registration. Some comparative studies with other algorithms have also been discussed. The paper ends with a discussion of the developments in medical image registration algorithms post mutual information, which primarily include deep neural network (DNN) based algorithms.(c) 2021 Elsevier B.V. All rights reserved.

Automated summary

Image registration, the process of aligning one image in the coordinate system of another, plays a vital role in the medical field. Mutual information-based algorithms have significantly advanced medical image registration, and new developments, including deep neural network-based algorithms, continue to emerge. This paper provides a survey of these algorithms, discussing their development, major works, comparative studies, and the post-mutual information era in medical image registration.