Smartphone-Based Dual-Modality Imaging System for Quantitative Detection of Color or Fluorescent Lateral Flow Immunochromatographic Strips

Nanoscale Research Letters

Wei Tao¹  Yafei Hou¹  Kun Xiao¹  Daxiang Cui¹  Weijian Qin¹  Kan Wang¹  Wenting Lu² 

[1] Department of Instrument Science and Engineering, School of Electronic Information and Electrical Engineering, Shanghai Jiao Tong University;Zhujiang Hospital, Southern Medical University;

关键词: Smartphone;    Dual-modality imaging;    Lateral flow strip;    Quantitative detection;   

DOI  :  10.1186/s11671-017-2078-9

来源: DOAJ

【 摘 要 】

Abstract Nowadays, lateral flow immunochromatographic assays are increasingly popular as a diagnostic tool for point-of-care (POC) test based on their simplicity, specificity, and sensitivity. Hence, quantitative detection and pluralistic popular application are urgently needed in medical examination. In this study, a smartphone-based dual-modality imaging system was developed for quantitative detection of color or fluorescent lateral flow test strips, which can be operated anywhere at any time. In this system, the white and ultra-violet (UV) light of optical device was designed, which was tunable with different strips, and the Sobel operator algorithm was used in the software, which could enhance the identification ability to recognize the test area from the background boundary information. Moreover, this technology based on extraction of the components from RGB format (red, green, and blue) of color strips or only red format of the fluorescent strips can obviously improve the high-signal intensity and sensitivity. Fifty samples were used to evaluate the accuracy of this system, and the ideal detection limit was calculated separately from detection of human chorionic gonadotropin (HCG) and carcinoembryonic antigen (CEA). The results indicated that smartphone-controlled dual-modality imaging system could provide various POC diagnoses, which becomes a potential technology for developing the next-generation of portable system in the near future.

【 授权许可】

Unknown