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

R. Khosla, C. Lai, Yasue 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 publicationIEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings
PublisherIEEE Computer Society
Pages163-168
Number of pages6
Volume2003-January
ISBN (Print)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

Other

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

Fingerprint

Soft computing
Cells
Distributed parameter control systems
Image processing
Tissue
Neural networks
Control systems
Water

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

Cite this

Khosla, R., Lai, C., & Mitsukura, Y. (2003). Optimising the performance of soft computing agents for classification of unstained mammalian cell images. In IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings (Vol. 2003-January, pp. 163-168). [1227221] IEEE Computer Society. https://doi.org/10.1109/CIMSA.2003.1227221

Optimising the performance of soft computing agents for classification of unstained mammalian cell images. / Khosla, R.; Lai, C.; Mitsukura, Yasue.

IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings. Vol. 2003-January IEEE Computer Society, 2003. p. 163-168 1227221.

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

Khosla, R, Lai, C & Mitsukura, Y 2003, Optimising the performance of soft computing agents for classification of unstained mammalian cell images. in IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings. vol. 2003-January, 1227221, IEEE Computer Society, pp. 163-168, 2003 IEEE International Symposium on Computational Intelligence for Measurement Systems and Applications, CIMSA 2003, Lugano, Switzerland, 03/7/29. https://doi.org/10.1109/CIMSA.2003.1227221
Khosla R, Lai C, Mitsukura Y. Optimising the performance of soft computing agents for classification of unstained mammalian cell images. In IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings. Vol. 2003-January. IEEE Computer Society. 2003. p. 163-168. 1227221 https://doi.org/10.1109/CIMSA.2003.1227221
Khosla, R. ; Lai, C. ; Mitsukura, Yasue. / Optimising the performance of soft computing agents for classification of unstained mammalian cell images. IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings. Vol. 2003-January IEEE Computer Society, 2003. pp. 163-168
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