Denoising and deblurring gold immunochromatographic strip images via gradient projection algorithms
Gold immunochromatographic strip (GICS) assay provides a quick, convenient, single-copy and on-site approach to determine the presence or absence of the target analyte when applied to an extensive variety of point-of-care tests. It is always desirable to quantitatively detect the concentration of tr...
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| Published in | Neurocomputing (Amsterdam) Vol. 247; pp. 165 - 172 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Elsevier B.V
19.07.2017
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| Subjects | |
| Online Access | Get full text |
| ISSN | 0925-2312 1872-8286 |
| DOI | 10.1016/j.neucom.2017.03.056 |
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| Abstract | Gold immunochromatographic strip (GICS) assay provides a quick, convenient, single-copy and on-site approach to determine the presence or absence of the target analyte when applied to an extensive variety of point-of-care tests. It is always desirable to quantitatively detect the concentration of trace substance in the specimen so as to uncover more useful information compared with the traditional qualitative (or semi-quantitative) strip assay. For this purpose, this paper is concerned with the GICS image denoising and deblurring problems caused by the complicated environment of the intestine/intrinsic restrictions of the strip characteristics and the equipment in terms of image acquisition and transmission. The gradient projection approach is used, together with the total variation minimization approach, to denoise and deblur the GICS images. Experimental results and quantitative evaluation are presented, by means of the peak signal-to-noise ratio, to demonstrate the performance of the combined algorithm. The experimental results show that the gradient projection method provides robust performance for denoising and deblurring the GICS images, and therefore serves as an effective image processing methodology capable of providing more accurate information for the interpretation of the GICS images. |
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| AbstractList | Gold immunochromatographic strip (GICS) assay provides a quick, convenient, single-copy and on-site approach to determine the presence or absence of the target analyte when applied to an extensive variety of point-of-care tests. It is always desirable to quantitatively detect the concentration of trace substance in the specimen so as to uncover more useful information compared with the traditional qualitative (or semi-quantitative) strip assay. For this purpose, this paper is concerned with the GICS image denoising and deblurring problems caused by the complicated environment of the intestine/intrinsic restrictions of the strip characteristics and the equipment in terms of image acquisition and transmission. The gradient projection approach is used, together with the total variation minimization approach, to denoise and deblur the GICS images. Experimental results and quantitative evaluation are presented, by means of the peak signal-to-noise ratio, to demonstrate the performance of the combined algorithm. The experimental results show that the gradient projection method provides robust performance for denoising and deblurring the GICS images, and therefore serves as an effective image processing methodology capable of providing more accurate information for the interpretation of the GICS images. |
| Author | Zeng, Nianyin Dobaie, Abdullah M. Zhang, Hong Li, Yurong Liang, Jinling |
| Author_xml | – sequence: 1 givenname: Nianyin surname: Zeng fullname: Zeng, Nianyin email: zny@xmu.edu.cn, nianyin.zeng@gmail.com organization: Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, Fujian 361005, China – sequence: 2 givenname: Hong surname: Zhang fullname: Zhang, Hong organization: Department of Instrumental and Electrical Engineering, Xiamen University, Xiamen, Fujian 361005, China – sequence: 3 givenname: Yurong surname: Li fullname: Li, Yurong organization: College of Electrical Engineering and Automation, Fuzhou University, Fuzhou 350002, China – sequence: 4 givenname: Jinling surname: Liang fullname: Liang, Jinling organization: School of Mathematics, Southeast University, Nanjing 210096, China – sequence: 5 givenname: Abdullah M. surname: Dobaie fullname: Dobaie, Abdullah M. organization: Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah 21589, Saudi Arabia |
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| SubjectTerms | Gradient projection Image deblurring Image denoising Lateral flow immunoassay Total variation |
| Title | Denoising and deblurring gold immunochromatographic strip images via gradient projection algorithms |
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