Medical image ensemble registration based on Gaussian mixture model and color component regularization

被引:0
|
作者
Hu, Shun-bo [1 ]
Orchard, Jeff [2 ]
机构
[1] Linyi Univ, Sch Informat, Linyi 276005, Peoples R China
[2] Univ Waterloo, David R Cheriton Sch Comp Sci, Waterloo, ON N2L 3G1, Canada
来源
OPTIK | 2015年 / 126卷 / 01期
基金
中国国家自然科学基金;
关键词
Ensemble registration; Color medical image registration; Gaussian mixture model (GMM); Color components regularization; GROUPWISE REGISTRATION; NONRIGID REGISTRATION;
D O I
10.1016/j.ijleo.2014.06.176
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
Ensemble registration has proven to be more robust and accurate than competing pairwise registration methods. Color medical images are commonly applied in medical diagnosis and analysis. In this paper ensemble registration using a Gaussian mixture model is extended from gray images to color medical images. To decrease the transformation differences among color component deformations of the same image, the color component regularization term is incorporated into ensemble registration and a novel total cost function is proposed. Color ensemble registration is implemented to gastroscope images and brain cryosection images. The experimental results show that our color ensemble registration can successfully align color ensemble images with stable color component's transformation. (C) 2014 Elsevier GmbH. All rights reserved.
引用
收藏
页码:6 / 12
页数:7
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