“虚拟中国人男性一号”多模态图像配准  被引量:2

Virtual Chinese Human(Male No.1) Multimodality Image Registration

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作  者:张杰[1] 龚辉[1] 曾绍群[1] 骆清铭[1] 刘谦[1] 

机构地区:[1]华中科技大学生物医学光子学教育部重点实验室武汉光电国家实验室(筹),湖北武汉430074

出  处:《中国医学物理学杂志》2007年第5期329-332,318,共5页Chinese Journal of Medical Physics

基  金:863计划(2006AA02Z343)资助项目

摘  要:目的:解决"虚拟中国人男性一号"CT图像、MRI图像与断层切削图像之间的多模态图像配准问题。材料和方法:根据这三种图像的特点,选择CT图像为基准图像,在对MRI图像进行配准时,通过求解两幅图像梯度特征的最大互信息,搜索出最佳配准参数;在对断层切削图像进行配准时,采用基于解剖结构特征提取的配准方法获取最佳配准参数;最后,根据所得配准参数对待配图进行变换,从而达到配准目的。结果:对头部三种模态图像数据集进行了配准,与高精度手工分割图像数据集进行对比,配准正确率达到95.8%。结论:配准结果准确,解决了"虚拟中国人男性一号"多模态图像配准问题,为数字化虚拟人多模态图像配准提供了参考。Objective: To solve the multimodality image registration methods of three images data (CT, MRI and color slice image) of Virtual Chinese Human (VCH). Materials and Methods: According to the features of these three images, CT image was chosen as the reference image, when MRI images were registed, the best match parameter was searched by discriminating the largest mutual information between the two kinds of images gradient; while at the image registration of color slice image, the best match parameter was obtained by image segmentation. In the end, images were transformed on the basis of the best match parameters. Results: Three images of different modality data were registed, and compared with high-quality manual segmentation image datasets, registration accurate rate is 95.8%. Conclusions: Multimodality image registration of three images can be accomplished exactly using this methods, it provides reference for multimodality image registration of digital human.

关 键 词:图像配准 多模态图像 互信息 虚拟中国人 

分 类 号:R322[医药卫生—人体解剖和组织胚胎学]

 

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