Zhang Qiang, Wang Lei, Qian Qing, Wang Jishuai, Cheng Wenbo, Han Kun
Academy for Engineering & Technology, Fudan University, Shanghai 200433, P. R. China.
CAS Key Laboratory of Bio-Medical Diagnostics, Suzhou Institute of Biomedical Engineering and Technology, Chinese Academy of Sciences, Suzhou 215163, P. R. China.
ACS Omega. 2020 Aug 3;5(32):20100-20106. doi: 10.1021/acsomega.0c01733. eCollection 2020 Aug 18.
Bio-optical imaging can noninvasively describe specific biochemical reaction events in small animals using endogenous or exogenous imaging reagents to label cells, proteins, or DNA. The fluorescence optical bio-imaging system excites the fluorescent group to a high energy state by excitation light and then generates emission light. However, many substances in the organism will also emit fluorescence after being excited by the excitation light, and the nonspecific fluorescence generated will affect the detection sensitivity. This paper designs and develops a set of high-level biosafety in vivo fluorescence imaging system for small animals suitable for virology research and proposes a target area extraction algorithm for fluorescence images. The fluorescence image target extraction algorithm first maps the nonlinear separation data in the low-dimensional space to the high-dimensional space. Then, based on the analysis of the characteristics of the fluorescent region, a method for discriminating the target fluorescent region based on the two-step entropy function is proposed, and the real target fluorescent region is obtained according to the set connected region. Based on the experiment of collecting and analyzing the in vivo fluorescent images of mice, it is verified that the proposed algorithm can automatically extract the target fluorescent region better than the classical linear model. It shows that the proposed algorithm is less affected by background fluorescence, and the estimated separated spectrum based on this method is closer to the real target spectrum.
生物光学成像可以使用内源性或外源性成像试剂标记细胞、蛋白质或DNA,以非侵入性方式描述小动物体内特定的生化反应事件。荧光光学生物成像系统通过激发光将荧光基团激发到高能态,然后产生发射光。然而,生物体内的许多物质在被激发光激发后也会发出荧光,产生的非特异性荧光会影响检测灵敏度。本文设计并开发了一套适用于病毒学研究的小动物体内高水平生物安全荧光成像系统,并提出了一种荧光图像目标区域提取算法。该荧光图像目标提取算法首先将低维空间中的非线性分离数据映射到高维空间。然后,基于对荧光区域特征的分析,提出了一种基于两步熵函数的目标荧光区域判别方法,并根据设定的连通区域得到真实的目标荧光区域。通过对小鼠体内荧光图像的采集和分析实验,验证了所提算法比经典线性模型能更好地自动提取目标荧光区域。结果表明,所提算法受背景荧光影响较小,基于该方法估计的分离光谱更接近真实目标光谱。