期刊文献+
共找到1篇文章
< 1 >
每页显示 20 50 100
A novel denoising framework for cerenkov luminescence imaging based on spatial information improved clustering and curvature-driven diffusion 被引量:1
1
作者 Xin Cao Yi Sun +5 位作者 Fei Kang Lin Wang Huangjian Yi Fengjun Zhao Linzhi Su Xiaowei He 《Journal of Innovative Optical Health Sciences》 SCIE EI CAS 2018年第4期35-42,共8页
With widely availed clinically used radionuclides,Cer enkov luminescence imaging(CLI)has become a potential tool in the field of optical molecular imaging.However,the impulse noises introduced by high-energy gamma ray... With widely availed clinically used radionuclides,Cer enkov luminescence imaging(CLI)has become a potential tool in the field of optical molecular imaging.However,the impulse noises introduced by high-energy gamma rays that are generated during the decay of radionuclide reduce the image quality significantly,which affects the acauracy of quantitative analysis,as well as the three dimensional reconstruction.In this work,a novel denoising framework based on fuzzy dlustering and curvat ure driven difusion(CDD)is proposed to remove this kind of impulse noises.To improve the accuracy,the F u1zzy Local Information C-Means algorithm,where spatial information is evolved,is used.We evaluate the per formance of the proposed framework sys-tematically with a series of experiments,and the corresponding results demonstrate a better denoising effect than those from the commonly used median filter method.We hope this work may provide a useful data pre processing tool for CLI and its following studies. 展开更多
关键词 cerenkov luminescence imaging image processing radionuclide imaging
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部