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

Author

Khosla, R. ; Lai, C. ; Mitsukura, Y.

Author_Institution

Sch. of Bus., La Trobe Univ., Melbourne, Vic., Australia

fYear

2003

fDate

29-31 July 2003

Firstpage

163

Lastpage

168

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.

Keywords

biological tissues; cellular biophysics; distributed control; image classification; image segmentation; intelligent control; medical image processing; multi-agent systems; control system model; human tissue; image processing; morphological agents; multiagent distributed control system model; neural networks; pathological conditions; performance optimisation; segmentation; soft computing agents; stained image analysis; symbiotic relationship; unstained Chinese hamster ovarian image samples; unstained mammalian cell images classification; water immersion; Computer networks; Control system synthesis; Distributed control; Humans; Image analysis; Image processing; Image segmentation; Neural networks; Pathology; Symbiosis;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence for Measurement Systems and Applications, 2003. CIMSA '03. 2003 IEEE International Symposium on

Print_ISBN

0-7803-7783-4

Type

conf

DOI

10.1109/CIMSA.2003.1227221

Filename

1227221