北京生物医学工程2011，Vol.30Issue(4)：344-349,6.DOI:10.3969/j.issn.1002-3208.2011.04.04
动态磁共振成像中利用时空滤波的非笛卡尔稀疏数据重建新算法
One New Algorithm of Utilizing Spatio-Temporal Filtering for the Reconstruction of Non-Cartesian Sparse Data in Dynamic MRI
摘要
Abstract
Sparsely non-Cartesian sampling indicates a promising future for dynamic magnetic resonance imaging ( MRI ) because it can shorten acquisition time remarkably. Current reconstruction algorithms for dynamic images mainly utilize signal correlations in temporal domain , which insufficiently use the signal correlations in spatial domain. We proposed a new algorithm for the reconstruction of non-Cartesian sparse data in dynamic MRI, which exploited signal correlations in time to circumvent data sparsity and employed high-frequency enhancement in k-space to emphasize edge sharpness. Simulated experiments showed that this proposed approach allowed k-space based reconstruction results with good temporal resolution and spatial resolution of non-Cartesian sparse data in dynamic MRI.关键词
动态磁共振图像/非笛卡尔/稀疏/Hanning滤波/高频增强Key words
dynamic magnetic resonance imaging/ non-Cartesian/ sparse/ Hanning filter/ high frequency enhancement分类
医药卫生引用本文复制引用
梅颖洁,周爱珍,王聪,莫纪江,陈武凡,冯衍秋..动态磁共振成像中利用时空滤波的非笛卡尔稀疏数据重建新算法[J].北京生物医学工程,2011,30(4):344-349,6.基金项目
国家973项目(2010CB732502)及国家自然科学基金(30800254)资助 （2010CB732502）
