Research of New Coloration Biochip Reader Based on Charge-coupled Device_Journal of Biomedical Engineering

Authors：

1. Shanghai Institute of Technology, Shanghai 201418, China;
2. Shanghai Baio Technology Co. Ltd, Shanghai 200233, China;
3. Shanghai Mediworks Precision Instrument Co. Ltd, Shanghai 201100, China;

Corresponding author：

Keywords：

coloration biochip; charge-coupled device; i.MX6; microarray image processing

DOI：

10.7507/1001-5515.20160114

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Abstract Full text Figures/Tables Video References Cited by

Aiming at long signal acquisition time, low flux, bad signal-to-noise ratio and low intelligence in coloration biochip reader, a new kind of rapid device with high flux was developed. The device consisted of hardware system and software system. It used a charge-coupled device (CCD) as the photoelectric sensor elements and obtained the biochip microarray image. The device integrated the embedded operating system based on i.MX6 chip. The microarray image processing, data analysis and result output were achieved through the code information of the software chip. Experiments with the standard grayscale sheet and standard format chip were carried out. The results showed that the maximum measurement error was less than 0.1%, the value of R² was 98.7%, and the value of CV was 1.096 1%. The comparison results of 200 samples showed that detection performance of the proposed device was better than that of the same kind of marketed equipment.

Citation： LUEnze, LINZhisong, ZHUBin, WEIYue, XINGJunfen. Research of New Coloration Biochip Reader Based on Charge-coupled Device. Journal of Biomedical Engineering, 2016, 33(4): 691-697. doi: 10.7507/1001-5515.20160114 Copy

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1. 张文毓.生物芯片产业发展现状及展望[J].传感器世界, 2007, 13(10):6-10.
2. 王立强, 陆祖康, 林斌.生物芯片及其荧光信号检测[J].光学仪器, 2002, 24(4-5):7-13.
3. RACHLIN D J. Optimized approach for microarray scanning[J]. Proc SPIE, 2002, 4623:7-13.
4. 张帆, 薛利军, 李自田, 等.基于CCD的生物芯片扫描分析系统的设计[J].光子学报, 2006, 35(4):565-568.
5. 国家食品药品监督管理总局, 国家食品药品监督管理总局数据库[DB/OL]. (2014-10-26)[2015-10-10]. http://app1.sfda.gov.cn/datasearch/face3/dir.html.
6. 邢军芬, 汪涛, 张莹, 等.CYP2C19显色型基因芯片的研究[J].中国医药生物技术, 2015, 10(1):39-44.
7. BAJCSY P. An overview of DNA microarray image requirements for automated processing[C]//IEEE Computer Society Conference on Computer Vision and Pattern Recognition. San Diego, CA, USA:2005:147.
8. FENSTERMACHER D. Introduction to bioinformatics[J]. Journal of the American Society for Information Science and Technology, 2005, 56(5):440-446.
9. 胡园园, 孙啸, 何农跃, 等.基于图像投影的基因芯片图像网格定位[J].生物医学工程学杂志, 2005, 22(4):668-671.
10. GONZALEZ R C, WOODS R E. Digital image processing[M]. 2nd ed. Beijing:Publishing House of Electronics Industry, 2003.
11. PETERS R A. A new algorithm for image noise-reduction using mathematical morphology[J]. IEEE Transactions on Image Processing, 1995, 4(5):554-568.
12. 王树文, 闫成新, 张天序, 等.数学形态学在图像处理中的应用[J].计算机工程与应用, 2004, 40(32):89-92.
13. YE Q H, QIN L X, FORGUES M, et al. Predicting hepatitis B virus-positive metastatic hepatocellular carcinomas using gene expression profiling and supervised machine learning[J]. Nat Med, 2003, 9(4):416-423.
14. VARENHORST C, JAMES S, ERLINGE D, et al. Genetic variation of CYP2C19 affects both pharmacokinetic and pharmacodynamic responses to clopidogrel but not prasugrel in aspirin-treated patients with coronary artery disease[J]. Eur Heart J, 2009, 30(14):1744-1752.

Journal of Biomedical Engineering

Research of New Coloration Biochip Reader Based on Charge-coupled Device

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