A survey on mutual information based medical image registration algorithms

被引:26
|
作者
Sengupta, Debapriya [1 ]
Gupta, Phalguni [2 ]
Biswas, Arindam [1 ]
机构
[1] Indian Inst Engn Sci & Technol, Howrah, India
[2] GLA Univ, Mathura, India
关键词
Mutual information; Medical image registration; Entropy; Joint entropy; PROBABILISTIC NEURAL-NETWORKS; DEFORMABLE REGISTRATION; 3-DIMENSIONAL REGISTRATION; FUNCTION APPROXIMATION; LEARNING ALGORITHM; FEATURE-EXTRACTION; MR-IMAGES; OPTIMIZATION; PET; MAXIMIZATION;
D O I
10.1016/j.neucom.2021.11.023
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:174 / 188
页数:15
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