Medical image elastic registration based on discontinuity adaptive Markov random field model

被引:0
|
作者
Lu, Z. T. [1 ]
Feng, Q. J. [1 ]
Zhou, S. J. [2 ]
He, L. F. [3 ]
Chen, W. F. [1 ]
机构
[1] So Med Univ, Sch Biomed Engn, Guangzhou 510515, Guangdong, Peoples R China
[2] Chinese Peoples Liberat Army Gen Hosp, Beijing 100853, Peoples R China
[3] Aichi Prefectural Univ, Fac Informat Sci & Technol, Aichi 4801198, Japan
来源
IMAGING SCIENCE JOURNAL | 2010年 / 58卷 / 04期
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
elastic registration; discontinuity adaptive Markov random field model; B-spline; maximum a posteriori; NONRIGID REGISTRATION; DEFORMATION;
D O I
10.1179/136821910X12694455411025
中图分类号
TB8 [摄影技术];
学科分类号
0804 ;
摘要
We present a novel elastic registration algorithm using discontinuity adaptive Markov random field (DA-MRF) model. We use B-spline to model the deformation field, and then the coefficients of B-spline are the parameters to be evaluated. We model the coefficients fields as MRFs. The optimal deformation is sought as maximum a posteriori (MAP) configurations through a minimisation problem that includes two terms: the pixel-wise mean-square distance measure between the reference and the warped test image (data term), and continuity constraints imposed on pairs of neighbouring coefficients that promotes a smooth deformation (regularisation term). We use two-and three-dimensional medical images to test the proposed algorithm. Experimental results show that the proposed method is robust and accurate, suitable for clinical application.
引用
收藏
页码:193 / 201
页数:9
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