Improved scoring and semi-automatic screening of human peripheral blood chromosomes by CNN visual system

Author

Tompa, A. ; Szirányi, T. ; Nemes, L. ; Rekeczky, Cs ; Roska, T.

Author_Institution

Dept. of Genotoxicology, Nat. Inst. of Occupational Health, Budapest, Hungary

fYear

1996

Firstpage

99

Lastpage

102

Abstract

Many of the microscopic image processing tasks can be well implemented in the cellular neural net Universal Machine (CNN UM) architecture. We have developed a complex system for chromosome analysis. Our method, when implemented in hardware containing VLSI chips, can execute some important image processing steps at superior speed. The recent simulator based system is capable of helping the reliable chromosome analysis

Keywords

VLSI; biological techniques; biology computing; blood; cellular biophysics; cellular neural nets; digital signal processing chips; image classification; image recognition; medical image processing; optical microscopy; CNN visual system; Universal Machine; VLSI chips; cellular neural net; chromosome analysis; human peripheral blood chromosomes; image processing steps; microscopic image processing tasks; scoring; semi-automatic screening; Analytical models; Biological cells; Cellular neural networks; Hardware; Humans; Image processing; Microscopy; Neural networks; Turing machines; Very large scale integration;

fLanguage

English

Publisher

ieee

Conference_Titel

Cellular Neural Networks and their Applications, 1996. CNNA-96. Proceedings., 1996 Fourth IEEE International Workshop on

Conference_Location

Seville

Print_ISBN

0-7803-3261-X

Type

conf

DOI

10.1109/CNNA.1996.566501

Filename

566501