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.
Cite
@article{arxiv.1810.09707,
title = {Cell detection on image-based immunoassays},
author = {Pol del Aguila Pla and Joakim Jaldén},
journal= {arXiv preprint arXiv:1810.09707},
year = {2018}
}
Comments
5 pages, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), Washington, DC, USA, April 4-7, 2018