Segmentation of microspheres in ultrahigh density multiplexed microsphere-based assays

Abhishek Mathur*, David M Kelso

*Corresponding author for this work

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

1 Scopus citations

Abstract

We have developed a method to identify and localize luminescent microspheres in dense images of microsphere-based assays. Application of this algorithm to the images of densely packed microspheres would aid in increasing the number of assays per unit target sample volume by several orders of magnitude. We immobilize or sediment microspheres on microscope slides and read luminescence from these randomly arrayed microspheres with a digital imaging microscope equipped with a cooled CCD camera. Our segmentation algorithm, which is based on marker-controlled watershed transformation, is then implemented to segment the microsphere clusters in the luminescent images acquired at different wavelengths. This segmentation algorithm is fully automated and require no manual intervention or training sets for optimizing the parameters and is much more accurate than previously proposed algorithms. Using this algorithm, we have accurately segmented more than 97% of the microspheres in dense images.

Original languageEnglish (US)
Title of host publicationImage Processing
Subtitle of host publicationAlgorithms and Systems, Neural Networks, and Machine Learning - Proceedings of SPIE-IS and T Electronic Imaging
Volume6064
DOIs
StatePublished - Apr 17 2006
EventImage Processing: Algorithms and Systems, Neural Networks, and Machine Learning - San Jose, CA, United States
Duration: Jan 16 2006Jan 18 2006

Other

OtherImage Processing: Algorithms and Systems, Neural Networks, and Machine Learning
CountryUnited States
CitySan Jose, CA
Period1/16/061/18/06

Keywords

  • Cluster segmentation
  • Fully automated
  • Image analysis
  • Microsphere-based assays
  • Watershed

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Condensed Matter Physics
  • Computer Science Applications
  • Applied Mathematics
  • Electrical and Electronic Engineering

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