Title :
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
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;
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
DOI :
10.1109/CNNA.1996.566501
