Optimising the performance of soft computing agents for classification of unstained mammalian cell images

R. Khosla, C. Lai, Y. Mitsukura

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

Abstract

Most existing approaches for determining serious pathological conditions involve analysis of stained images of human tissue. In this paper we describe a multi-agent distributed control system model for image processing of unstained human (mammalian) cell images. The control system model develops a symbiotic relationship between soft computing agents like neural networks and water immersion and morphological agents for segmentation and classification of cells in unstained Chinese hamster ovarian image samples.

Original languageEnglish
Title of host publicationCIMSA 2003 - 2003 IEEE International Symposium on Computational Intelligence for Measurement Systems and Applications
PublisherIEEE Computer Society
Pages163-168
Number of pages6
ISBN (Electronic)0780377834
DOIs
Publication statusPublished - 2003
Externally publishedYes
Event2003 IEEE International Symposium on Computational Intelligence for Measurement Systems and Applications, CIMSA 2003 - Lugano, Switzerland
Duration: 2003 Jul 292003 Jul 31

Publication series

NameIEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings
Volume2003-January
ISSN (Print)2159-1547
ISSN (Electronic)2159-1555

Other

Other2003 IEEE International Symposium on Computational Intelligence for Measurement Systems and Applications, CIMSA 2003
Country/TerritorySwitzerland
CityLugano
Period03/7/2903/7/31

Keywords

  • Computer networks
  • Control system synthesis
  • Distributed control
  • Humans
  • Image analysis
  • Image processing
  • Image segmentation
  • Neural networks
  • Pathology
  • Symbiosis

ASJC Scopus subject areas

  • Artificial Intelligence
  • Control and Systems Engineering

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