It is the cache of ${baseHref}. It is a snapshot of the page. The current page could have changed in the meantime.
Tip: To quickly find your search term on this page, press Ctrl+F or ⌘-F (Mac) and use the find bar.

A Novel Image Methodology for Interpretation of Gold Immunochromatographic Strip | Li | Journal of Computers
Journal of Computers, Vol 6, No 3 (2011), 540-547, Mar 2011
doi:10.4304/jcp.6.3.540-547

A Novel Image Methodology for Interpretation of Gold Immunochromatographic Strip

Yurong Li, Nianyin Zeng, Min Du

Abstract


Gold immunochromatographic strip assay is a rapid, simple, single-copy and on-site method. Quantitative Interpretation of the strip can provide more information than the traditional qualitative or semiquantitative strip assay. The paper aims to develop an image based assay method for quantitative determination of trace concentrations by gold immunochromatographic strip. The image of gold immunochromatographic strip is taken by CCD, and, after the proper filter and window cutting, the test line and control line is segmented by the genetic fast fuzzy c-means(FCM) clustering algorithm. In order to improve the measure property, based on Lambert-beer law, the relative reflective integral optical density(RIOD) is selected as the feature by which the interference in the test and control lines can be canceled out each other. The proposed method is applied to the quantitative detection of human chorionic gonadotropin (hCG) as a model. Firstly, the segmentation performance of the genetic fast FCM clustering algorithm is compared with threshold method and FCM clustering algorithm in terms of the peak signal-to-noise ratio (PSNR). Furthermore, the comparison of the blind experiment between the proposed method and commercial quantitative instrument swp-sc1 is carried out. This method is shown to deliver a result comparable and even superior to existing techniques.



Keywords


gold immunochromatographic strip; quantitative interpretation; adaptive segmentation; genetic fast fuzzy c-means

References


[1] J. Zhu, W. Chen, Y. Lu, G. Cheng, “Development of an immunochromatographic assay for the rapid detection of bromoxynil in water,” Environmental Pollution, vol. 156(1), pp. 136-142, November 2008.
doi:10.1016/j.envpol.2007.12.020
PMid:18255209

[2] Zh. Yan, L. Zhou, Y. Zhao, J. Wang, L.H Huang, K.X Hu, “Rapid quantitative detection of Yersinia pestis by lateral-flow immunoassay and up-converting phosphor technology-based biosensor.” Sensors and Actuators B.vol.119(2),pp.656–663, December 2006.
doi:10.1016/j.snb.2006.01.029

[3] H. Uto, A. Ido, K. Kusumoto, S. Hasuike, K. Nagata and et al.“Development of a rapid semi-quantitative immunochromatographic assay for serum hepatocyte growth factor and its usefulness in acute liver failure,” Hepatology Research. vol.33(4), pp. 272-276, December 2005.
doi:10.1016/j.hepres.2005.08.011
PMid:16293443

[4] D. Peng, S. Hu, Y. Hua, Y. Xiao Z. Li,X. Wang and et al. “Comparison of a new gold-immunochromatographic assay for the detection of antibodies against avian influenza virus with hemagglutination inhibition and agar gel immunodiffusion assays,” Veterinary Immunology and Immunopathology, vol.117(1-2), pp. 17-25, May,2007.
doi:10.1016/j.vetimm.2007.01.022
PMid:17337303

[5] S. Huang, H. Wei, Y. Lee,“One-step immunochro-matographic assay for the detection of Staphylococcus aureus,”Food Control, Vol. 18(8), pp. 893-897, 2007.
doi:10.1016/j.foodcont.2006.05.005

[6] J. Chandler, T.Gurmin T, and N.Robinson, “The place of gold in rapid tests,” IVD Technology. vol. 6(2), pp.37-49, March,2000.

[7] L Chuang, J.Y Hwang, H.CH Chang, F.M Chang, and SH.B Jong, “Rapid and simple quantitative measurement of a-fetoprotein by combining immunochromatographic strip test and artificial neural network image analysis system,” Clinica Chimica Acta. vol. 348, pp.87–93, October, 2004.
doi:10.1016/j.cccn.2004.05.010
PMid:15369740

[8] PA Benn,"Advances in prenatal screening for Down syndrome: I. general principles and second trimester testing," Clin. Chim. Acta. vol.323 (1-2),pp: 1–16, September,2002.
doi:10.1016/S0009-8981(02)00186-9

[9] D. Li, S. Wei, H. Yang, Y. Li, and A. Deng, “A sensitive immunochromatographic assay using colloidal gold–antibody probe for rapid detection of pharmaceutical indomethacin in water samples,” Biosensors and Bioelectronics. vol. 24(7), pp. 2277-2280,March,2009.
doi:10.1016/j.bios.2008.11.004
PMid:19097880

[10] J. Kaur, K. Singh, R. Boro, K. Thampi, M. Raje, and G. Varshney, “Immunochromatographic dipstick assay format using gold nanoparticles labeled protein-hapten conjugate for the detection of atrazine,” Environmental Science and Technology. vol. 41(14), pp. 5028–5036,June,2007.
doi:10.1021/es070194j

[11] R. Tanaka, T. Yuhi, N. Nagatani, T. Endo,K. Kerman, and Y. Takamura, “A novel enhancement assay for immunochromatographic test strips using gold nanoparticles,” Anal Bioanal Chem. vol. 385(8), pp. 1414–1420, July,2006.
doi:10.1007/s00216-006-0549-4
PMid:16838160

[12] M. Du and ZH. Fang, “Research of the quantitative test instrument for colloidal-gold strips,” Chinese Journal of Scientific Instrument. vol. 22(6), pp. 626-629, December,2001.

[13] L. Huang, A. Zeng, Y. Zhang, B. Ren,K. Yu, and H. Huang, “Development of reflectance photom eter for gold-labeled test strip,” Chinese Journal of Scientific Instrument. vol. 30(3), pp. 663-667,March,2009.

[14] M. DU, F. Yang, and H. Fei, “Application of photoelectric sensor to quantitative determination of immunochro-matographic assay strip,” Chinese Journal of Scientific Instrument. vol. 36(7), pp. 671-673,July,2005.

[15] K.Faulstich, R.Gruler, M.Eberhard, and K.Haberstroh, “Developing rapid mobile POC systems. Part 1:Devices and applications for lateral-flow immunodiagnostics,” IVD Technology. vol.13(6):47–53, July,2007.

[16] K.Faulstich, R.Gruler, M.Eberhard, and K.Haberstroh, “Developing rapid mobile POC systems. Part 2: Nucleic acid based testing platforms,” IVD Technology. vol.13(7):47, September,2007.

[17] E. Sumonphan, S. Auephanwiriyakul, N. Theera-Umpon, “Interpretation of nevirapine concentration from immunochromatographic strip test using support vector regression,” Proceedings of 2008 IEEE International Conference on Mechatronics and Automation,pp.633-637,August,2008.
doi:10.1109/ICMA.2008.4798830

[18] M. Forouzanfar, N. Forghani, M. Teshnehlab,“Parameter optimization of improved fuzzy c-means clustering algorithm for brain MR image segmentation,” Engineering Applications of Artificial Intelligence. vol. 23(2), pp. 160-168, March,2010.
doi:10.1016/j.engappai.2009.10.002

[19] Y. Li, Y. Shen,“An automatic fuzzy c-means algorithm for image segmentation,” Soft Computing. vol. 14(2), pp. 123-128, January,2010.
doi:10.1007/s00500-009-0442-0

[20] ZH. Zhang, Y. Zhang, ZH. Ma, and X. Wang, “ An averaging-based adaptive filter,” Journal of Image and Graphics. vol. 5(6), pp. 530-534,June,2000.

[21] X. Zhou, Q. Shen, L. Liu, “ An improved FCM method based on particle swarm optimization for color image segmentation,” Journal of Computational Information Systems. vol. 4(5), pp. 2097-2102, October,2008.

[22] R. Hathaway., Y Hu, “Density-weighted fuzzy c-means clustering hathaway,” IEEE Transactions on Fuzzy Systems, Vol.17(1),pp.243-252,February, 2009.
doi:10.1109/TFUZZ.2008.2009458

[23] ZH. Huang, Y. Xie, D. Liu, L. Hou, “Using Fuzzy C-means Cluster for Histogram-Based Color Image Segmentation,” 2009 International Conference on Information Technology and Computer Science, Vol.1, pp.597-600,2009.
doi:10.1109/ITCS.2009.130

[24] H. Lau, T. Chan, W. Tsui, W. Pang, “Application of genetic algorithms to solve the multidepot vehicle routing problem,” IEEE Transactions on Automation Science and Engineering, Vol.7(2), pp.383 -392,April,2010.
doi:10.1109/TASE.2009.2019265

[25] C. De, B. Chakraborty, “Acoustic characterization of seafloor sediment employing a hybrid method of neural network architecture and fuzzy algorithm,” IEEE Geoscience and Remote Sensing Letters, Vol. 6 (4),pp. 743 -747,October,2009.
doi:10.1109/LGRS.2009.2024438

[26] J. Ingle and S. Crouch, Spectrochemical Analysis. Prentice Hall, New Jersey, 1988.

[27] B. Zineddin, Z. Wang, K. Fraser, and X. Liu, “Investigation on filtering cDNA microarray image based multiview anaalysis,” in the 14th International Conference on Automation & Computing, S. Zhang and D. Li, Eds. London, UK: Pacilantic International Ltd., 2008, pp. 201-206.

[28] K. Fraser, Z. Wang, and X. Liu, Microarray Image Analysis. Chapman & Hall/CRC, London, February, 2010.

[29] B. Zineddin, Z. Wang, Y. Li, M. Du, Y. Shi and X. Liu, “A novel neural network approach to cDNA microarray image segmentation,” unpublished.


Full Text: PDF


Journal of Computers (JCP, ISSN 1796-203X)

Copyright @ 2006-2014 by ACADEMY PUBLISHER – All rights reserved.