A Hybrid Optimization Method for Maximum Mutual Information Registration

被引：2

作者：

Pan, Xiaoguang ^{[1
]}

Zhao, Kai ^{[1
]}

Liu, Jiren ^{[1
]}

Kang, Yan ^{[2
]}

机构：

[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Peoples R China

[2] Northeastern Univ, Informat Engn Sch, Sino-Dutch Biomed, Shenyang, Peoples R China

来源：

2010 3RD INTERNATIONAL CONFERENCE ON BIOMEDICAL ENGINEERING AND INFORMATICS (BMEI 2010), VOLS 1-7 | 2010年

关键词：

maximum mutual information; hybrid optimization method; incremental coordinate transformation method; multi-resolution; MULTIMODALITY IMAGE REGISTRATION;

D O I：

10.1109/BMEI.2010.5639449

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Maximum mutual information (MI) is widely used in multimodality registration. However, traditional registration based on MI is difficult to be adopted in clinical routine for its time-consuming. We proposed a hybrid optimization method which can reduce time for one evaluation of the MI criterion by using incremental coordinate transformation method and also can reduce the whole iteration time by using multi-resolution as the search strategy. The performance of the hybrid optimization method was evaluated for rigid-body registration of CT and PET images of the same patient, and the results showed the hybrid method was faster than traditional maximum mutual information method.

引用

页码：18 / 22

页数：5