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基于空间信息改进聚类的切伦科夫荧光图像去噪算法

Denoising Algorithm of Cerenkov Luminescence Images Based on Spatial Information Improved Clustering

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摘要

切伦科夫荧光成像因具有临床上广泛可用的放射性核素探针而成为近年来光学分子影像领域的研究热点,但放射性核素在衰变过程中产生的大量高能射线会造成采集到的切伦科夫荧光图像上存在大量脉冲噪声,严重影响基于切伦科夫荧光图像的定量分析和后续的三维重建等。为了尽可能降低上述噪声,提出了一种结合模糊局部信息C-均值聚类算法和整体变分模型的切伦科夫荧光图像去噪算法。数值仿真、物理仿体以及真实动物实验结果表明:与现阶段广泛使用的中值滤波算法相比,所提去噪算法能够在有效去除噪声的同时保留切伦科夫荧光光源部位的形状细节。

Abstract

With a widely available clinical radionuclide probe, Cerenkov luminescence imaging becomes one of the hot research topics in the field of optical molecular imaging. However, a large number of pulse noises on Cerenkov luminescence image, which are produced during the decay of radionuclide, seriously affect the following researches based on Cerenkov luminescence images, such as quantitative analysis, 3D reconstruction and so on. To suppress these pulse noises, we propose a denoising algorithm based on fuzzy local information C-means clustering algorithm and total variation model. The numerical simulation experiment, physical phantom experiment and animal experiment demonstrate that compared to the common used median filter algorithm, the proposed algorithm can remove the impulse noised effectively with the ability of maintaining the shape of Cerenkov Luminescence source.

Newport宣传-MKS新实验室计划
补充资料

中图分类号:TP391;Q63

DOI:10.3788/aos201838.1017001

所属栏目:医用光学与生物技术

基金项目:国家自然科学基金(61601363,11571012,61701403)、陕西省自然科学基础研究计划(2017JQ6017,2017JQ6006)、陕西省教育厅项目(16JK1772,17JF027)、中国博士后科学基金(2016M602851)、西北大学研究生自主创新项目(YZZ17172)

收稿日期:2018-03-29

修改稿日期:2018-05-02

网络出版日期:2018-05-07

作者单位    点击查看

贺小伟:西北大学信息科学与技术学院, 陕西 西安 710127
孙怡:西北大学信息科学与技术学院, 陕西 西安 710127
卫潇:西北大学信息科学与技术学院, 陕西 西安 710127
卢笛:西北大学信息科学与技术学院, 陕西 西安 710127
曹欣:西北大学信息科学与技术学院, 陕西 西安 710127
侯榆青:西北大学信息科学与技术学院, 陕西 西安 710127

联系人作者:贺小伟(hexw@nwu.edu.cn); 曹欣(xin_cao@163.com); 孙怡(sunyi@stumail.nwu.edu.cn);

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引用该论文

He Xiaowei,Sun Yi,Wei Xiao,Lu Di,Cao Xin,Hou Yuqing. Denoising Algorithm of Cerenkov Luminescence Images Based on Spatial Information Improved Clustering[J]. Acta Optica Sinica, 2018, 38(10): 1017001

贺小伟,孙怡,卫潇,卢笛,曹欣,侯榆青. 基于空间信息改进聚类的切伦科夫荧光图像去噪算法[J]. 光学学报, 2018, 38(10): 1017001

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