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Pixel sensible local band analysis in microscopic chromosome images using CSPA

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Abstract

In chromosome analysis, local band analysis plays the main role to identify the perfect matched chromosome in metaspread images to attain the karyotyping. Literature investigations are narrow in chromosome image band analysis due to the higher complexities. In this paper, Pixel level based Conditional Seed Point Algorithm (CSPA) is proposed. This simulation algorithm separates the weak band region to the strong band region, and the strong band region area evaluated was based on the Region of Seed condition Points. This algorithm works well for different intensity levels and adopts the structural changes to identify the bands in image. This algorithm was simulated in more than 450 individual chromosomes to identify the local bands in the chromosome images and provided the accuracy more than 96%.

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References

  1. Arthur, D.C. and Bloomfield, C.D., Partial deletion of the long arm of chromosome 16 and bone marrow eosinophilia in acute nonlymphocytic leukemia, Blood, 1983, vol. 61, no. 5, pp. 994–998.

    CAS  PubMed  Google Scholar 

  2. Speicher, M.R., Gwyn S., Ballard S., and Ward, D.C., Karyotyping: human chromosomes by combinatorial multi-flour fish, Nat. Genet., 1996, vol. 12, no. 4, pp. 368–375.

    Article  CAS  PubMed  Google Scholar 

  3. Schrock, E., Manoir, S., Veldman, T., Schoell, B., Wienberg, J., Ferguson-Smith, M.A., Ning, Y., Ledbetter, D.H., Bar-Am, I., Soenksen, D., Garini, Y., and Ried, T., Multicolor spectral karyotyping of human chromosomes, Science, 1996, vol. 273, pp. 494–497.

    Article  CAS  PubMed  Google Scholar 

  4. Adams, R. and Bischof, L., Seeded region growing, IEEE Transactions Pattern Analysis and Machine Intelligence, 1994, vol. 16, no. 6, pp. 641–647.

    Article  Google Scholar 

  5. Panwar, P. and Gulati, N., Genetic algorithms for image segmentation using active contours, J. Global Res. Comp. Sci., 2013, vol. 4, no. 1, pp. 34–37.

    Google Scholar 

  6. Karvelis, P.S., Fotiadis, D.I., Georgiou, I., and Syrrou, M., A watershed based segmentation method for multispectral chromosome images classification, in Proc. 28 IEEE EMBS Ann. Int. Conf., New York City, 2006, pp. 3009–3012.

    Google Scholar 

  7. Malyszko, D. and Wierzchon, S.T., Standard and genetic k-means clustering techniques in image segmentation, in IEEE 6th Int. Conf. on Computer Information Systems and Industrial Management Applications (CISIM’07), 2007, 0-7695-2894-5/07.

    Google Scholar 

  8. Carothers, A. and Piper, J., Computer-aided classification of human chromosomes: a review, Statistics Computing, 1994, vol. 4, no. 3, pp. 161–171.

    Article  Google Scholar 

  9. Ledley, R.S., Ing, P.S., and Lubs, H.A., Human chromosome classification using discriminant analysis and Bayesian probability, Comput. Biol. Med., 1980, vol. 10, no. 4, pp. 209–219.

    Article  CAS  PubMed  Google Scholar 

  10. Lerner, B., Toward a completely automatic neural network based human chromosome analysis, IEEE Trans. Systems Man Cybernet., 1998, vol. 28, pp. 544–552.

    Article  CAS  Google Scholar 

  11. Yang, X., Wen, D., Cui, Y., Cao, X., Lacny, J., and Tseng, C., Computer based karyotyping, in IEEE Third Int. Conf. on Digital Soc., 2009, 978-0-7695-3526-5/09.

    Google Scholar 

  12. Groen, F.C.A., Kate, T.K., Smeulders, A.W.M., and Young, I.T., Human chromosome classification based on local band descriptors, Pattern Recognition Lett., 1989, pp. 211–222.

    Google Scholar 

  13. Kao, J., Chuang, J., and Wang, T., Chromosome classification based on the band profile similarity along approximate medial axis, Pattern Recognition, 2008, vol. 41, no. 1, pp. 77–89.

    Article  Google Scholar 

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Correspondence to D. Somasundaram.

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Somasundaram, D. Pixel sensible local band analysis in microscopic chromosome images using CSPA. Cytol. Genet. 50, 42–46 (2016). https://doi.org/10.3103/S0095452716010084

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  • DOI: https://doi.org/10.3103/S0095452716010084

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