Multimodal Medical Image Registration Based on Gradient Vector Flow and Particle Swarm Optimization
- VernacularTitle:基于梯度矢量流与粒子群优化算法的多模态医学图像配准
- Author:
Qi ZHANG
;
Yuanyuan WANG
- Publication Type:Journal Article
- Keywords:
image registration;
multimodal medical images;
gradient vector flow;
particle swarm optimization
- From:Space Medicine & Medical Engineering
2006;0(06):-
- CountryChina
- Language:Chinese
-
Abstract:
Objective To study the method based on gradient vector flow (GVF) and particle swarm optimization (PSO) for realizing multimodal medical image registration and improving its accuracy. Methods In view of three major components of image registration, i.e. the feature space, the similarity metric and the search strategy, a novel method was proposed with three improvements. Firstly, the GVF field was employed as the feature space. Then three similarity metrics were proposed based on GVF field. Finally, an improved PSO combined with crossover mechanism of genetic algorithm was utilized to search for the optimal transformation of two images. Results With 54 times of experiments on both simulated and real medical images, it was demonstrated that this method accurately registered the multimodal medical images to be superior to the method based on PSO of pixels, and the Walsh transform method. Conclusion The method based on GVF and PSO is effective for multimodal medical image registration.
