Cell detection on image-based immunoassays

Cell detection and counting in the image-based ELISPOT and Fluorospot immunoassays is considered a bottleneck. The task has remained hard to automatize, and biomedical researchers often have to rely on results that are not accurate. Previously proposed solutions are heuristic, and data-based solutio...

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Bibliographic Details
Published in2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018) pp. 431 - 435
Main Authors del Aguila Pla, Pol, Jalden, Joakim
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.04.2018
Subjects
Adsorption
Analytical models
Convolution
Data models
Electrical Engineering
Elektro- och systemteknik
Immune system
Immunoassays
Inverse problems
Mathematical model
Optimization
Source localization
Technology and Health
Teknik och hälsa
Two dimensional displays
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Summary:Cell detection and counting in the image-based ELISPOT and Fluorospot immunoassays is considered a bottleneck. The task has remained hard to automatize, and biomedical researchers often have to rely on results that are not accurate. Previously proposed solutions are heuristic, and data-based solutions are subject to a lack of objective ground truth data. In this paper, we analyze a partial differential equations model for ELISPOT, Fluorospot, and assays of similar design. This leads us to a mathematical observation model for the images generated by these assays. We use this model to motivate a methodology for cell detection. Finally, we provide a real-data example that suggests that this cell detection methodology and a human expert perform comparably.
ISBN:9781538636367
1538636352
9781538636374
1538636379
1538636360
9781538636350
ISSN:1945-8452
DOI:10.1109/ISBI.2018.8363609