3D平移不变剪切波域统计相关性驱动的多模态医学图像融合方法研究

项目名称： 3D平移不变剪切波域统计相关性驱动的多模态医学图像融合方法研究

项目编号： No.61502282

项目类型： 青年科学基金项目

立项/批准年度： 2016

项目学科： 计算机科学学科

项目作者： 王雷

作者单位： 山东理工大学

项目金额： 20万元

中文摘要： 基于多尺度几何变换理论的医学图像融合方法是当前的研究热点，它对于帮助医生综合利用不同模态的医学信息，制定准确的放疗手术方案具有重要意义。然而，此类方法目前还存在所用几何变换工具对高维特征信息稀疏表示能力较弱，融合规则缺失不同尺度、不同方向子带系数间统计相关性的缺点。因此，本课题根据多尺度几何变换理论的发展趋势，提出基于3D平移不变剪切波变换的融合算法；针对统计相关性缺失的问题，基于多分辨率统计分析理论，研究3D平移不变剪切波系数的统计性质，揭示其存在强烈统计相关性的特点，建立子带系数的统计相关模型，提出基于多尺度、多方向统计相关性驱动的融合规则，阐明利用统计相关性提高融合性能的机理。该课题拟从几何变换工具的稀疏表示能力和在融合规则中嵌入统计相关性两方面改进传统的融合方法，对多分辨率统计分析理论的发展和利用多模态医学图像融合技术提高放疗手术的成功率具有重要的理论研究意义和广阔的应用价值。

中文关键词： 图像融合；3D；剪切波变换；平移不变；统计相关性；医学图像

英文摘要： Multi-scale geometric transformation based multi-modality medical image fusion method has become the current research focus, and it is of great meanings for doctors to make accurate radiotherapy by comprehensively utilizing the medical information from different modalities. The currently existing medical image fusion methods, however, usually suffer from the weak sparse representation ability of the selected geometric transformation tools for the high-dimensional feature information and the loss of statistical dependency correlation between the coefficients of different scales and different directions. Therefore, according to the orientation of the multi-scale geometric transformation theory, this project will propose 3D shift-invariant shearlet transformation based medical image fusion method. For the loss of the statistical dependency, this project will reveal the strong existence of the statistical dependency between the 3D shearlet coefficients by the multi-resolution statistical analysis theory and build a statistical dependency model to describe the dependent relationship. Furthermore, the fusion rule driven by the multi-scale and direction dependency is also to be developed to clarify the mechanism that how to improve the fusion performance by making use of the strongly statistical dependency. The proposed method will improve the performance of the traditional fusion methods from the point view of the sparse representation ability and the embedding of the statistical dependency in the fusion rule. Therefore, it is of great significance and application value for the development of the multi-resolution statistical analysis theory and the improvement of the success rate of the radiotherapy by using multi-modal medical image fusion technology.

英文关键词： Image Fusion;3D Shearlet Transform;Shift-Invariant;Statistical Dependencey;Medical Image