Extraction of ideogram features for diagnosing chromosomal abnormalities

2022;
: pp. 22-25
1
National Aviation University
2
National Aviation University

This paper proposes an approach to the detection and extraction of specific features in an ideogram image. Ideogram is a depiction of a healthy chromosome used in a karyotyping process - a procedure designed to diagnose chromosomal abnormalities.

Extraction of ideogram features is a part of a general algorithm for the detection of chromosomal abnormlities. According to the general algorithm, both chromosomes and ideograms have to be parsed and converted into a single data format for further comparison.

The image of the ideogram is the input data for the algorithm of the extraction of ideogram features, which is proposed in this paper. The output is a data structure containing ideogram properties. A software prototype has been developed to verify the algorithm efficiency.

  1. C. O'Connor, “Chromosome mapping: Idiograms”, https://www.nature.com/scitable/topicpage/chromosome-mapping-idiograms-302/, 2008.
  2. C. O'Connor, “Karyotyping for Chromosomal Abnormalities”, https://www.nature.com/scitable/topicpage/karyotyping-for-chromosomal-abnormalities-298/, 2008.
  3. O. Pysarchuk and Y. Mironov, “Chromosome Feature Extraction and Ideogram-Powered Chromosome Categorization”, Advances in Computer Science for Engineering and Education. Lecture Notes on Data Engineering and Communications Technologies, vol 134, pp 427–436, Springer, Cham. 2022. https://doi.org/10.1007/978-3-031-04812-8_36
  4. O. Pysarchuk, Y. Mironov, “Decision support system for medical pathology recognition”, Science-Based Technologies, vol. 49 No. 1, pp. 13-22, 2021. (Ukrainian) https://doi.org/10.18372/2310-5461.49.15287
  5. S. Moorthie, et al, “Congenital Disorders Expert Group. Chromosomal disorders: estimating baseline birth prevalence and pregnancy outcomes worldwide“, Journal of Community Genetics, vol. 9(4), pp. 377-386, 2018. https://doi.org/10.1007/s12687-017-0336-2
  6. X. Zhang, et al, “Cytogenetic Analysis of the Products of Conception After Spontaneous Abortion in the First Trimester“, Cytogenetic and Genome Research, vol. 161, pp. 120-131, 2021. https://doi.org/10.1159/000514088
  7. R. Nandakumar and KB Jayanthi, “Feature Extraction for the Classification of Human Chromosomes from G-Band Images using Wavelets”, International Journal of Engineering Research & Technology (IJERT) ICEECT, no 8(17), pp. 67-72, 2020.
  8. M. Moradi and K. Setarehdan, “New features for automatic classification of human chromosomes: A feasibility study”, Pattern Recognition Letters, vol. 27(1), pp. 19-28, 2006. https://doi.org/10.1016/j.patrec.2005.06.011
  9. S. Kumar, A. Kiso, and N. Abenthung Kithan, “Chromosome Banding and Mechanism of Chromosome Aberrations,” Cytogenetics - Classical and Molecular Strategies for Analysing Heredity Material, Jul. 2021. https://doi.org/10.5772/intechopen.96242
  10. A. Buades, B. Coll, J. Morel, “Non-Local Means Denoising”, IPOL Journal, vol. 1, pp. 208-212, 2021. https://doi.org/10.5201/ipol.2011.bcm_nlm
  11. “Median Filter”,  https://en.wikipedia.org/wiki/Median_filter, Nov 21, 2022.