Rigid medical image registration and its association with mutual information

被引:5
作者
Fookes, C
Bennamoun, M
机构
[1] Queensland Univ Technol, Sch Elect Elect & Syst Engn, Brisbane, Qld 4001, Australia
[2] Univ Western Australia, Dept Comp Sci & Software Engn, Crawley, WA 6009, Australia
关键词
computer vision; mutual information; rigid registration; medical images;
D O I
10.1142/S0218001403002800
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Image registration plays a crucial role in the computer vision and medical imaging field where it is used to develop a spatial mapping between different sets of data. These transformations can range from simple rigid registrations to complex nonrigid deformations. Mutual information (MI) is a popular entropy-based similarity measure which has recently experienced a prolific expansion in a number of image registration applications. Stemming from information theory, this measure generally outperforms most other intensity-based measures in multimodal applications as it only assumes a statistical dependence between images. This paper provides a thorough introduction to the MI measure and its use in rigid medical image registration. A look at the extensions proposed to the original measure will also be provided. These were developed to improve the robustness of the measure and to avoid certain cases when maximizing MI does not lead to the correct spatial alignment.
引用
收藏
页码:1167 / 1206
页数:40
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