中国组织工程研究与临床康复2010，Vol.14Issue(39)：7407-7410,4.DOI:10.3969/j.issn.1673-8225.2010.39.046
自适应正则化超分辨率MR图像重建
Self-adaptive regularized super-resolution reconstruction of magnetic resonance images
徐启飞 1张怀国 2王厚军 1王建华1
作者信息
- 1. 临沂市人民医院,影像科,山东省临沂市,276000
- 2. 临沂市人民医院,内分泌科,山东省临沂市,276000
- 折叠
摘要
Abstract
BACKGROUND: Super-resolution reconstruction has been extensively studied and used in many fields,such as medical diagnostics,military surveillance,frame freeze in video,and remote sensing.OBJECTIVE: In order to obtain high-resolution magnetic resonance images,gradient magnetic field is required and the signal-to-noise will be reduced due to the decrease in voxel size with traditional scan.The present study used a self-adaptive regularized super-resolution reconstruction algorithm to acquire high-resolution magnetic resonance images from four half-pixel-shifted low resolution images.METHODS: The least squares algorithm was used as a cost function.The dedvative of the cost function was calculated to obtain an iterative formula of super-resolution reconstruction.In the process of iterative process,the parameter and step size of image resolution were regularized.RESULTS AND CONCLUSION: The new regularization parameter makes cost function of the new algorithm convex within the definition region.The piori information is involved in the regularization parameter that can improve the high-frequency components of the restored image.As shown from the results obtained in the phantom imaging,the proposed super-resolution technique can improve the resolution of magnetic resonance image.关键词
自适应/MR图像/超分辨率重建/迭代/正则化参数分类
医药卫生引用本文复制引用
徐启飞,张怀国,王厚军,王建华..自适应正则化超分辨率MR图像重建[J].中国组织工程研究与临床康复,2010,14(39):7407-7410,4.
