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Cell detection on image-based immunoassays
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0003-3054-7210
KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.ORCID iD: 0000-0001-6630-243X
2018 (English)Conference paper, Published paper (Refereed)
Abstract [en]

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 forthe 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.

Place, publisher, year, edition, pages
IEEE, 2018.
Keyword [en]
Inverse problems, Optimization, Source localization, Immunoassays
National Category
Signal Processing Medical Image Processing
Research subject
Technology and Health; Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-223933OAI: oai:DiVA.org:kth-223933DiVA, id: diva2:1190619
Conference
IEEE International Symposium on Biomedical Imaging (ISBI 2018), Washington, D.C., April 4-7, 2018
Funder
Swedish Research Council, 2015-04026
Note

QC 20180319

Available from: 2018-03-15 Created: 2018-03-15 Last updated: 2018-03-26Bibliographically approved

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del Aguila Pla, PolJaldén, Joakim

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
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Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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