Paper Info
Title
Cell Detection On Image-Based Immunoassays
Abstract
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.
Year
DOI
Venue
2018
10.1109/ISBI.2018.8363609
2018 IEEE 15TH INTERNATIONAL SYMPOSIUM ON BIOMEDICAL IMAGING (ISBI 2018)
Keywords
Field
DocType
Inverse problems, Optimization, Source localization, Immunoassays
Signal processing,Bottleneck,Heuristic,Pattern recognition,Computer science,ELISPOT,Image based,FluoroSpot,Ground truth,Source localization,Artificial intelligence
Conference
ISSN
Citations 
PageRank 
1945-7928
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Pol del Aguila Pla102.03
Joakim Jalden224321.59