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

R. Khosla; C. Lai; Yasue Mitsukura

doi:10.1109/CIMSA.2003.1227221

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

Research output: Chapter in Book/Report/Conference proceeding › Conference 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 language	English
Title of host publication	IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings
Publisher	IEEE Computer Society
Pages	163-168
Number of pages	6
Volume	2003-January
ISBN (Print)	0780377834
DOIs	https://doi.org/10.1109/CIMSA.2003.1227221
Publication status	Published - 2003
Externally published	Yes
Event	2003 IEEE International Symposium on Computational Intelligence for Measurement Systems and Applications, CIMSA 2003 - Lugano, Switzerland Duration: 2003 Jul 29 → 2003 Jul 31

Other

Other	2003 IEEE International Symposium on Computational Intelligence for Measurement Systems and Applications, CIMSA 2003
Country	Switzerland
City	Lugano
Period	03/7/29 → 03/7/31

Fingerprint

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 proceeding › Conference 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

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Access to Document

10.1109/CIMSA.2003.1227221