Lateral Flow Test Interpretation with Residual Networks

A Smartphone-Based Platform Assisted by Artificial Intelligence for Reading and Reporting Rapid Diagnostic Tests: Evaluation Study in SARS-CoV-2 Lateral Flow Immunoassays

“…The algorithm performed as well in RDT brands that were not used at all for training purposes, making the solution suitable for other RDTs, including other diseases. Compared with previous studies [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21], our system is able to identify individual bands of the RDTs, allowing for complex result reading and sending them in real-time to a cloud platform. A requirement and limitation of the proposed system is the correct acquisition of the image (acquisition error in the field studies was <0.8%).…”

“…Combining RDTs with digital tools, artificial intelligence (AI) and mobile health approaches can help standardize result interpretation and facilitate immediate reporting and monitoring of results [5]. Several works have been proposed to automatically interpret photographs of RDTs using different image processing approaches, from classical methods, such as morphology-based methods, to more sophisticated machine learning or deep learning methods [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21]. Nevertheless, these approaches are not capable of handling 2-band and 3-band RDTs indistinctly, are not connected to a cloud platform that enables the collection of mass screening results, and many require additional hardware.…”