NDLI: A New Approach to Automatic Classification of the Curved Chromosomes

Content Provider	IEEE Xplore Digital Library
Author	Javan-Roshtkhari, M. Setarehdan, S.K.
Copyright Year	2007
Description	Author affiliation: Univ. of Tehran, Tehran (Javan-Roshtkhari, M.; Setarehdan, S.K.)
Abstract	In this paper, an effective algorithm for chromosome image processing for straightening the curved chromosomes is presented. This is a very helpful procedure which extends the domain of success of most of the previously reported algorithms to highly curved chromosomes. The procedure is based on the calculation and analyzing the vertical and horizontal projection vectors of the binary image of the chromosome. The binary image is obtained by thresholding the input image after histogram modification. When applied to the real chromosome images the proposed algorithm could straighten all of the highly bent curved chromosomes within the image dataset. To assess the effectiveness of proposed algorithm, a neural network based chromosome classification system is developed. Wavelet transform domain features are extracted and used in an MLP structure for this purpose and a classification rate of 95.3% is obtained.
Starting Page	19
Ending Page	24
File Size	4673759
Page Count	6
File Format	PDF
ISBN	9789531841160
ISSN	18455921
DOI	10.1109/ISPA.2007.4383657
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-09-27
Publisher Place	Turkey
Access Restriction	Subscribed
Rights Holder	Fac. of Elec. Eng. & Computing, Univ of Zagreb, Croatia
Subject Keyword	Biological cells Feature extraction Signal processing algorithms Image analysis Wavelet transforms Process control Intelligent control Microscopy Software packages Java Artificial neural networks Chromosome classification Projection vectors Wavelet transform
Content Type	Text
Resource Type	Article

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