Super-resolution Reconstruction of MR Image Based on Structure-adaptive Normalized Convolution

摘要：

To improve the signal-to-noise ratio and the resolution of MR image, this paper introduce structure-adaptive normalized convolution algorithm for image reconstruction from a series of repeatedly scanned MR images. The algorithm is based on the normalized convolution, which makes use of the local structure information to adjust filter parameters. Experimental results show that the algorithm can effectively enhance the resolution of image, while preserving the edge and detail of image.

关键词： Super-resolution MR image Normalized convolution Structure-adaptive

作者: Lin Tiemao Zheng Xuyuan Gu Xin

作者单位: School of Biomedical Engineering Tianjin Medical University Tianjin, China Department of Radiology The Affiliated Hospital of Medical College of Chinese Peoples Armed Police

会议类型: 国际会议

会议名称: 2010 IEEE 10th International Conference on Signal Processing(第十届信号处理国际会议 ICSP 2010)

会议地点: 北京

会议语种:英文

页码: 760-762

在线出版日期: 2010-08-24（万方平台首次上网日期，不代表论文的发表时间）