WANG Yu1,2, WANG Ming-quan1,2, YANG Xiao-feng3, WANG Yan-xiang1,2
(1. Key Laboratory of Instrumentation Science & Dynamic Measurement (North University of China), Ministry of Education, Taiyuan 030051, China; 2. School of Information and Communication Engineering, North University of China, Taiyuan 030051, China; 3. Shanxi Medical University, Taiyuan 030001, China)
Abstract: Infrared and visible light images can be obtained simultaneously by building fluorescence imaging system, which includes fluorescence excitation, images acquisition, mechanical part, image transmission and processing section. This system studied the 2 charge-coupled device (CCD) camera (AD-080CL) of the JAI company. Fusion algorithm of visible light and near infrared images was designed for the fluorescence imaging system with wavelet transform image fusion algorithm. In order to enhance the fluorescent moiety of the fusion image, the luminance value of the green component of the color image was changed. And using microsoft foundation classes (MFC) application architecture, the supporting software system was bulit in VS2010 environment.
Key words: fluorescence imaging system; image fusion; wavelet transform; microsoft foundation classes (MFC)
CLD number: TP391.41Document code: A
Article ID: 1674-8042(2016)02-0161-04 doi: 10.3969/j.issn.1674-8042.2016.02.011
References
[1]Coto-García A M, Sotelo-González E, Fernández-Argü-elles M T, et al. Nanoparticles as fluorescent labels for optical imaging and sensing in genomics and proteomics. Analytical & Bioanalytical Chemistry, 2011, 399(1): 29-42.
[2]LU Bi-bo, WANG Hui, MIAO Chun-li. Medical image fusion with adaptive local geometrical structure and wavelet transform. Procedia Environmental Sciences, 2011, 8: 262-269.
[3]Harada H, Kizaka-Kondoh S, Hiraoka M. Optical imaging of tumor hypoxia and evaluation of a hypoxiatargeting drug in living animals. Molecular Imaging, 2005, 4(3):182-193.
[4]Troyan S L, Kianzad V, Gibbs-Strauss S L, et al. The FLARE intraoperative near-infrared fluorescence imaging system: a first-in-human clinical trial in breast cancer sentinel lymph node mapping. Annals of Surgical Oncology, 2009, 16(10): 2943-2952.
[5]ZHENG Hong, ZHENG De-quan, HU Yan-xiang, et al. Study on the optimal parameters of image fusion based on wavelet transform. Journal of Computationgal Information Systems, 2010, 6(1): 131-137.
[6]Bradski G. Learning OpenCV. Beijing: Tsinghua University Press, 2009.
基于2CCD相机的荧光分子成像系统和融合算法
王玉1,2, 王明泉1,2, 杨晓峰3, 王艳翔1,2
(1. 中北大学 仪器科学与动态测试重点实验室, 山西 太原 030051; 2. 中北大学 信息与通信工程学院, 山西 太原 030051; 3. 山西医科大学, 山西 太原 030001)
摘要:本文通过建立荧光成像系统, 可以同时获得红外和可见光图像。 此荧光成像系统包括荧光激发部分、 图像获取部分、 机械部分、 图像传输和处理部分。 本系统主要研究了JAI公司的型号为AD-080CL的2CCD相机, 在荧光成像系统中设计了可见光和近红外图像融合算法, 采用小波变换融合方法。 为了增强融合图像中荧光部分的效果, 改变彩色图像中的绿色分量的亮度。 软件构架采用微软基础类库(MFC), 在VS2010下开发。
关键词:荧光成像系统; 图像融合; 小波变换; 微软基础类库(MFC)
引用格式:WANG Yu, WANG Ming-quan, YANG Xiao-feng, et al. Fluorescence molecular imaging system and fusion algorithm based on 2CCD camera. Journal of Measurement Science and Instrumentation, 2016, 7(2): 161-164. [doi: 10.3969/j.issn.1674-8042.2016.02.011]Vol.7 No.2, Jun. 2016Journal of Measurement Science and Instrumentation165HOU Hui-ling / Detail-preserving ring artifact correction method for cone-beam CTJournal of Measurement Science and InstrumentationVol.7 No.2, Jun. 2016
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