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 | |
| 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
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
}
TY - GEN
T1 - Optimising the performance of soft computing agents for classification of unstained mammalian cell images
AU - Khosla, R.
AU - Lai, C.
AU - Mitsukura, Yasue
PY - 2003
Y1 - 2003
N2 - 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.
AB - 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.
KW - Computer networks
KW - Control system synthesis
KW - Distributed control
KW - Humans
KW - Image analysis
KW - Image processing
KW - Image segmentation
KW - Neural networks
KW - Pathology
KW - Symbiosis
UR - http://www.scopus.com/inward/record.url?scp=84942565049&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84942565049&partnerID=8YFLogxK
U2 - 10.1109/CIMSA.2003.1227221
DO - 10.1109/CIMSA.2003.1227221
M3 - Conference contribution
AN - SCOPUS:84942565049
SN - 0780377834
VL - 2003-January
SP - 163
EP - 168
BT - IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Proceedings
PB - IEEE Computer Society
ER -