Chromosomes classification based on neural networks, fuzzy rule based, and template matching classifiers

Author

Bada, Ahmed M. ; Asan, Kahled ; Aly, Emam-Elha A. ; Messiha, Rimon A.

Author_Institution

Fac. of Eng., Cairo Univ.

Volume

1

fYear

2003

fDate

30-30 Dec. 2003

Firstpage

383

Abstract

A new features extraction algorithms for G-banded chromosomes classification system based on neural networks, fuzzy rule based and template matching classifiers are proposed. Chromosomes image is acquired and processed, geometrical features and gray-scale features are extracted for 872 chromosomes. Neural networks, fuzzy rule based, template matching classifiers results were compared. Classification rates are found to be over 99% for training and over 96% for testing sets

Keywords

biological techniques; cellular biophysics; feature extraction; fuzzy systems; image classification; image matching; medical image processing; neural nets; G-banded chromosomes classification system; chromosomes image; features extraction algorithms; fuzzy rule based classifiers; neural networks; template matching classifiers; Biological cells; Biomedical engineering; Design engineering; Feature extraction; Flowcharts; Fuzzy neural networks; Gray-scale; Image segmentation; Neural networks; Systems engineering and theory;

fLanguage

English

Publisher

ieee

Conference_Titel

Circuits and Systems, 2003 IEEE 46th Midwest Symposium on

Conference_Location

Cairo

ISSN

1548-3746

Print_ISBN

0-7803-8294-3

Type

conf

DOI

10.1109/MWSCAS.2003.1562299

Filename

1562299