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L. V. Guimaraes, J. A. Schuck and A. Elbern, “Chromosome Classification for Karyotype Composing Applying Shape Representation on Wavelet Packet Transform,” Proceedings of the 25th Annual International Conference of the IEEE EMBS, 2003, pp. 941-943.

has been cited by the following article:

• TITLE: Algorithms for Chromosome Classification

  AUTHORS: Wenzhong Yan, Lei Bai

  KEYWORDS: Chromosome; Classification; ANN; Wavelet; M-FISH

  JOURNAL NAME: Engineering, Vol.5 No.10B, December 17, 2013

  ABSTRACT: Automated chromosome classification has been an important pattern recognition problem for decades. In order to im-prove the performance of automated chromosome classification, artificial intelligence and machine learning methods have been widely used in the computer-assisted chromosome detection and classification systems. This paper is focused on these algorithms, especially on artificial neural network (ANN) and wavelet transform algorithms. The principle and the realization of these algorithms are analyzed. Results of these algorithms are compared and discussed.