Nonrigid medical image registration technique as a composition of local warpings

被引：9
|
作者：
Castellanos, NP [1 ]
Angel, PLD
Medina, V
机构：
[1] Univ Autonoma Metropolitana Iztapalapa, Elect Engn Dept, Mexico City 09340, DF, Mexico
[2] Ctr Invest & Matemat, Guanajuato 36240, Mexico
来源：
PATTERN RECOGNITION | 2004年 / 37卷 / 11期
关键词：
hybrid genetic algorithm; nonrigid image registration; nonlinear spatial transformation; normalized mutual information;
D O I：
10.1016/j.patcog.2003.09.019
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
We introduce a new technique for nonrigid image registration based on the composition of local deformations. The warping model is analyzed in order to guarantee continuity, differentiability and a one-to-one transformation by constraining the parameters of the nonlinear spatial transformation. A genetic algorithm solves the model by global optimization, handling constraints, and maximizing the normalized mutual information. The composition of local transformations goes throughout several levels of resolution, from coarse to fine. The performance of our technique was tested in synthetic and real medical images. The proposed method was always able to improve the similarity criterion between image pairs, demonstrating the robustness of the method for several modalities of images. (C) 2004 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
引用
收藏
页码：2141 / 2154
页数：14
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