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

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

A.M. Badawi, K.G. Hasan, E.-E.A. Aly and R.A. Messiha
2003 46th Midwest Symposium on Circuits and Systems, Vol.1, pp.383-387 Vol. 1
2003
DOI: https://doi.org/10.1109/MWSCAS.2003.1562299

Abstract

Biological cells Biomedical engineering Design engineering Feature extraction Flowcharts Fuzzy neural networks Gray-scale Image segmentation Neural networks Systems engineering and theory
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

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