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Conference paper

A Computer Vision Algorithm for the Digitalization of Colorimetric Lateral Flow Assay Readouts

In 2020 Symposium on Design, Test, Integration & Packaging of Mems and Moems (dtip) — 2020, pp. 1-6
From

Embedded Systems Engineering, Department of Applied Mathematics and Computer Science, Technical University of Denmark1

Department of Applied Mathematics and Computer Science, Technical University of Denmark2

Department of Biotechnology and Biomedicine, Technical University of Denmark3

Section for Microbial and Chemical Ecology, Department of Biotechnology and Biomedicine, Technical University of Denmark4

Lateral flow assays (LFAs) are low-cost testing tools widely used for home, point-of-care, or laboratory medical diagnostics. These tests typically use colorimetry to report the presence and the concentration of a certain physical/ biological quantity, showing the result as a color marker. This work presents a computer vision algorithm for the digitalization of LFA readouts, enabling precise and reliable results at low-cost.

The algorithm receives as input an image of a sample, identifies the color marker, and computes its average color intensity. In contrast to existing algorithms, the proposed one can detect color markers that are not characterized by a predetermined precise shape, size, and position, since the topology is identified and analyzed by the algorithm itself.

The evaluation of the proposed algorithm on a set of LFA strips shows correct functionality and execution time of less than a second.

Language: English
Publisher: IEEE
Year: 2020
Pages: 1-6
Proceedings: 2020 Symposium on Design, Test, Integration & Packaging of MEMS and MOEMS
ISBN: 1728189012 , 1728189020 , 9781728189017 and 9781728189024
Types: Conference paper
DOI: 10.1109/DTIP51112.2020.9139138
ORCIDs: Pezzarossa, Luca , Preus, Susan Ibi , Svendsen, Winnie Edith and Madsen, Jan

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