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Dicentric Chromosome Image Classification Using Fourier Domain Based Shape Descriptors and Support Vector Machine

  • Sachin PrakashEmail author
  • Nabo Kumar Chaudhury
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 460)

Abstract

Dicentric chromosomes can form in cells because of exposure to radioactivity. They differ from the regular chromosomes in that they have an extra centromere where the sister chromatids fuse. In this paper we work on chromosome classification into normal and dicentric classes. Segmentation followed by shape boundary extraction and shape based Fourier feature computation was performed. Fourier shape descriptor feature extraction was carried out to arrive at robust shape descriptors that have desirable properties of compactness and invariance to certain shape transformations. Support Vector Machine algorithm was used for the subsequent two-class image classification.

Keywords

Cytogenetic image analysis Shape-based classification Fourier shape descriptor 

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Copyright information

© Springer Science+Business Media Singapore 2017

Authors and Affiliations

  1. 1.Institute of Nuclear Medicine & Allied SciencesDelhiIndia

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