Detection and Categorisation of Multilevel High-Sensitivity Cardiovascular Biomarkers from Lateral Flow Immunoassay Images via Recurrent Neural Networks

Min Jing, Donal Mc Laughlin, David Steele, Sara Mc Namee, Brian Mac Namee, Patrick Cullen, Dewar Finlay, James McLaughlin

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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Abstract

Lateral Flow Immunoassays (LFA) have the potential to provide low cost, rapid and highly efficacious Point-of-Care (PoC) diagnostic testing in resource limited settings. Traditional LFA testing is semi-quantitative based on the calibration curve, which faces challenges in the detection of multilevel high-sensitivity biomarkers due its low sensitivity. This paper proposes a novel framework in which the LFA images are acquired from a designed CMOS reader system under controlled lighting. Unlike most existing approaches based on image intensity, the proposed system does not require detection of region of interest (ROI), instead each row of the LFA image was considered as time series signals. The Long Short-Term Memory (LSTM) network was deployed to classify the LFA data obtained from cardiovascular biomarker, C-Reactive Protein (CRP), at eight concentration levels (within the range 0-5mg/L) that are aligned with clinically actionable categories. The performance under different arrangements for input dimension and parameters were evaluated. The preliminary results show that the proposed LSTM outperforms other popular classification methods, which demonstrate the capability of the proposed system to detect high-sensitivity CRP and suggests the potential of applications for early risk assessment of cardiovascular diseases (CVD).
Original languageEnglish
Title of host publicationBIOIMAGING 2020 - 7th International Conference on Bioimaging, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020
Subtitle of host publicationProceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING
EditorsFilipe Soares, Ana Fred, Hugo Gamboa
Pages177-183
Number of pages7
Volume2
ISBN (Electronic)9789897583988
DOIs
Publication statusPublished - 29 Feb 2020
EventBIOIMAGING 2020 - , Malta
Duration: 24 Feb 202026 Feb 2020
http://www.bioimaging.biostec.org/

Publication series

NameBIOIMAGING 2020 - 7th International Conference on Bioimaging, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020

Conference

ConferenceBIOIMAGING 2020
CountryMalta
Period24/02/2026/02/20
Internet address

Keywords

  • Classification
  • High-sensitivity Cardiovascular Biomarkers
  • Lateral Flow Immunoassays (LFA) Image
  • Long Short-Term Memory (LSTM)
  • Point-of-Care (PoC)

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  • Cite this

    Jing, M., Mc Laughlin, D., Steele, D., Mc Namee, S., Mac Namee, B., Cullen, P., Finlay, D., & McLaughlin, J. (2020). Detection and Categorisation of Multilevel High-Sensitivity Cardiovascular Biomarkers from Lateral Flow Immunoassay Images via Recurrent Neural Networks. In F. Soares, A. Fred, & H. Gamboa (Eds.), BIOIMAGING 2020 - 7th International Conference on Bioimaging, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020: Proceedings of the 13th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 2: BIOIMAGING (Vol. 2, pp. 177-183). (BIOIMAGING 2020 - 7th International Conference on Bioimaging, Proceedings; Part of 13th International Joint Conference on Biomedical Engineering Systems and Technologies, BIOSTEC 2020). https://doi.org/10.5220/0009117901770183