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Proceedings Paper

Segmentation of microspheres in ultrahigh density multiplexed microsphere-based assays
Author(s): Abhishek Mathur; David M. Kelso
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Paper 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.

Paper Details

Date Published: 16 February 2006
PDF: 10 pages
Proc. SPIE 6064, Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning, 60640B (16 February 2006); doi: 10.1117/12.643170
Show Author Affiliations
Abhishek Mathur, Northwestern Univ. (United States)
David M. Kelso, Northwestern Univ. (United States)

Published in SPIE Proceedings Vol. 6064:
Image Processing: Algorithms and Systems, Neural Networks, and Machine Learning
Nasser M. Nasrabadi; Edward R. Dougherty; Jaakko T. Astola; Syed A. Rizvi; Karen O. Egiazarian, Editor(s)

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