Carrio Adrian, Sampedro Carlos, Sanchez-Lopez Jose Luis, Pimienta Miguel, Campoy Pascual
Computer Vision Group, Centre for Automation and Robotics (UPM-CSIC), Calle José Gutiérrez Abascal 2, Madrid 28006, Spain.
Aplitest Health Solutions, Paseo de la Castellana 164, Madrid 28046, Spain.
Sensors (Basel). 2015 Nov 24;15(11):29569-93. doi: 10.3390/s151129569.
Lateral flow assay tests are nowadays becoming powerful, low-cost diagnostic tools. Obtaining a result is usually subject to visual interpretation of colored areas on the test by a human operator, introducing subjectivity and the possibility of errors in the extraction of the results. While automated test readers providing a result-consistent solution are widely available, they usually lack portability. In this paper, we present a smartphone-based automated reader for drug-of-abuse lateral flow assay tests, consisting of an inexpensive light box and a smartphone device. Test images captured with the smartphone camera are processed in the device using computer vision and machine learning techniques to perform automatic extraction of the results. A deep validation of the system has been carried out showing the high accuracy of the system. The proposed approach, applicable to any line-based or color-based lateral flow test in the market, effectively reduces the manufacturing costs of the reader and makes it portable and massively available while providing accurate, reliable results.
如今，侧向流动分析测试正成为强大且低成本的诊断工具。获取结果通常需由操作人员对测试中的显色区域进行视觉解读，这会引入主观性以及结果提取中出现错误的可能性。虽然提供结果一致解决方案的自动化测试读取器广泛可得，但它们通常缺乏便携性。在本文中，我们展示了一种用于滥用药物侧向流动分析测试的基于智能手机的自动化读取器，它由一个廉价的灯箱和一部智能手机设备组成。用智能手机摄像头拍摄的测试图像在设备中使用计算机视觉和机器学习技术进行处理，以自动提取结果。已对该系统进行了深入验证，结果表明该系统具有很高的准确性。所提出的方法适用于市场上任何基于线条或基于颜色的侧向流动测试，有效降低了读取器的制造成本，使其具备便携性且大量可用，同时提供准确、可靠的结果。
