A smartphone-based rapid quantitative detection platform for lateral flow strip of human chorionic gonadotropin with optimized image algorithm

计算机科学 算法 检出限 人绒毛膜促性腺激素 图像处理 灰度 人工智能 图像(数学) 色谱法 化学 生物化学 激素
作者
Ting Zhang,Haibo Wang,Zi‐Tao Zhong,Chao-Qing Li,Wei Chen,Bo Liu,Yuan‐Di Zhao
出处
期刊:Microchemical Journal [Elsevier BV]
卷期号:157: 105038-105038 被引量:40
标识
DOI:10.1016/j.microc.2020.105038
摘要

Colloidal gold immunochromatographic test strip has been widely used as a rapid, simple and low-cost correct detection technology. However, its detection is often qualitative or semi-quantitative, which limits its clinical application to some extent. Herein, a portable test strip quantitative detection device based on smartphone to detect human chorionic gonadotropin (HCG) is developed. In experiment, a colloidal gold HCG detection strip based on antigen antibody immune response is constructed, and the quantitative results of three different image processing methods on the same strip detection are compared, including the threshold processing algorithm based on location information, the RGB color component extraction algorithm and the grayscale projection value processing algorithm, the results show that the last algorithm can realize the best recognition of the region of interest of strip. The mobile phone application software (App) based on this design shows that the detection limit of constructed colloidal gold HCG strip is 3 ng/mL with a linear range of 6–300 ng/mL. The detection result of real urine sample is consistent with the spiked concentration (R2 = 0.988), indicating that the concentration of HCG can be accurately measured in urine with this method, presenting the potential for instant diagnosis.
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