Extraction of Target Fluorescence Signal from In Vivo Background Signal Using Image Subtraction Algorithm  

作　　者：Liu, Fei  Liu, Xin  Zhang, Bin  Bai, Jing 

机构地区：[1] Department of Biomedical Engineering, School of Medicine, Tsinghua University, Beijing 100084, China

出　　处：《International Journal of Automation and computing》2012年第3期232-236,共5页国际自动化与计算杂志（英文版）

基　　金：supported by National Basic Research Program of China (973 Programme) (No. 2011CB707701);National Major Scientific Instrument and Equipment Development Project(No. 2011YQ030114);National Natural Science Foundation of China(Nos. 81071191, 60831003, 30930092, and 30872633);Beijing Natural Science Foundation (No. 3111003);Tsinghua-Yue-Yuen Medical Science Foundation

摘　　要：Challenges remain in fluorescence reflectance imaging (FRI) in in vivo experiments, since the target fluorescence signal is often contaminated by the high level of background signal originated from autofluorescence and leakage of excitation light. In this paper, we propose an image subtraction algorithm based on two images acquired using two excitation filters with different spectral regions. One in vivo experiment with a mouse locally injected with fluorescein isothiocyanate (FITC) was conducted to calculate the subtraction coefficient used in our studies and to validate the subtraction result when the exact position of the target fluorescence signal was known. Another in vivo experiment employing a nude mouse implanted with green fluorescent protein (GFP)—expressing colon tumor was conducted to demonstrate the performance of the employed method to extract target fluorescence signal when the exact position of the target fluorescence signal was unknown. The subtraction results show that this image subtraction algorithm can effectively extract the target fluorescence signal and quantitative analysis results demonstrate that the target-to-background ratio (TBR) can be significantly improved by 33.5 times after background signal subtraction.Challenges remain in fluorescence reflectance imaging (FRI) in in vivo experiments, since the target fluorescence signal is often contaminated by the high level of background signal originated from autofluorescence and leakage of excitation light. In this paper, we propose an image subtraction algorithm based on two images acquired using two excitation filters with different spectral regions. One in vivo experiment with a mouse locally injected with fluorescein isothiocyanate (FITC) was conducted to calculate the subtraction coefficient used in our studies and to validate the subtraction result when the exact position of the target fluorescence signal was known. Another in vivo experiment employing a nude mouse implanted with green fluorescent protein (GFP)—expressing colon tumor was conducted to demonstrate the performance of the employed method to extract target fluorescence signal when the exact position of the target fluorescence signal was unknown. The subtraction results show that this image subtraction algorithm can effectively extract the target fluorescence signal and quantitative analysis results demonstrate that the target-to-background ratio (TBR) can be significantly improved by 33.5 times after background signal subtraction.

关 键 词：Biomedical image processing biomedical optical imaging FLUORESCENCE fluorescence reflectance imaging imaging system. 

分 类 号：TN911.7[电子电信—通信与信息系统]