Symmetry-based detection of nuclei in microscopy images

Sundaresh Ram, Jeffrey J. Rodriguez

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

7 Scopus citations

Abstract

Accurate detection of individual cell nuclei in microscopic images is an essential task for many biological studies. Blur, clutter, bleed through, imaging noise and touching and partially overlapping nuclei with varying sizes and shapes make automated detection of individual cell nuclei a challenging task using image analysis. In this paper we propose an automated method for robust detection of individual cell nuclei in fluorescence in-situ hybridization (FISH) images obtained via confocal microscopy. Our algorithm consists of the following steps: image denoising, binarization, detection of nuclear seed points combining the fast radial symmetric transform (FRST) and a distance-based non-maximum suppression. We show that our algorithm provides improved detection accuracy compared to the existing algorithms.

Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Proceedings
Pages1128-1132
Number of pages5
DOIs
StatePublished - Oct 18 2013
Event2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013 - Vancouver, BC, Canada
Duration: May 26 2013May 31 2013

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Other

Other2013 38th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2013
CountryCanada
CityVancouver, BC
Period5/26/135/31/13

Keywords

  • FISH images
  • FRST
  • Nucleus detection
  • unimodal thresholding

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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