대한전기학회:학술대회논문집 (Proceedings of the KIEE Conference)
- 대한전기학회 1998년도 하계학술대회 논문집 B
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- Pages.555-559
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- 1998
계층형 신경회로망을 이용한 염색체 핵형 분류
Karyotype Classification of Chromosome Using the Hierarchical Neu
- Chang, Yong-Hoon (Dongju College) ;
- Lee, Young-Jin (Dong-A University) ;
- Lee, Kwon-Soon (Dong-A University)
- 발행 : 1998.07.20
초록
The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis have been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, We proposed an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of two-step multi-layer neural network(TMANN). We reconstructed chromosome image to improve the chromosome classification accuracy and extracted four morphological features parameters such as centromeric index (C.I.), relative length ratio(R.L.), relative area ratio(R.A.) and chromosome length(C.L.). These Parameters employed as input in neural network by preprocessing twenty human chromosome images. The experiment results shown that the chromosome classification error was reduced much more than that of the other classification methods.
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