Extraction of Ideogram Features for Diagnosing Chromosomal Abnormalities

dc.citation.epage25
dc.citation.issue2
dc.citation.journalTitleОбчислювальні проблеми електротехніки
dc.citation.spage22
dc.contributor.affiliationNational Aviation University
dc.contributor.authorПисарчук, Олексій
dc.contributor.authorМіронов, Юрій
dc.contributor.authorPysarchuk, Oleksii
dc.contributor.authorMironov, Yurii
dc.coverage.placenameЛьвів
dc.coverage.placenameLviv
dc.date.accessioned2025-03-06T07:20:22Z
dc.date.created2022-02-28
dc.date.issued2022-02-28
dc.description.abstractЗапропоновано підхід до розпізнавання зображень із хромосомними ідеограмами. Ідеограма – відображення здорової хромосоми, яке використовується під час каріотипування – процедури, розробленої для діагностування хромосомних аномалій. Розпізнавання ідеограм – частина загального алгоритму з діагностування хромосомних аномалій, згідно з яким хромосоми та ідеограми мають бути перетворені в єдиний формат даних для подальшого порівняння. Алгоритм розпізнавання ідеограм, що його запропоновано в цій публікації, приймає на вхід зображення ідеограми та повертає структуру даних, яка містить властивості ідеограми. Для підтвердження результативності алгоритму розроблено програмний прототип.
dc.description.abstractThis paper proposes an approach to the detection and extraction of specific features in an ideogram image. Ideogram is a depiction of a healthy chromosome [1] used in a karyotyping process – a procedure designed to diagnose chromosomal abnormalities [2]. Extraction of ideogram features is a part of a general algorithm for the detection of chromosomal abnormlities [3, 4]. 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.
dc.format.extent22-25
dc.format.pages4
dc.identifier.citationPysarchuk O. Extraction of Ideogram Features for Diagnosing Chromosomal Abnormalities / Oleksii Pysarchuk, Yurii Mironov // Computational Problems of Electrical Engineering. — Lviv : Lviv Politechnic Publishing House, 2022. — Vol 12. — No 2. — P. 22–25.
dc.identifier.citationenPysarchuk O. Extraction of Ideogram Features for Diagnosing Chromosomal Abnormalities / Oleksii Pysarchuk, Yurii Mironov // Computational Problems of Electrical Engineering. — Lviv : Lviv Politechnic Publishing House, 2022. — Vol 12. — No 2. — P. 22–25.
dc.identifier.doidoi.org/10.23939/jcpee2022.02.022
dc.identifier.urihttps://ena.lpnu.ua/handle/ntb/63935
dc.language.isoen
dc.publisherВидавництво Львівської політехніки
dc.publisherLviv Politechnic Publishing House
dc.relation.ispartofОбчислювальні проблеми електротехніки, 2 (12), 2022
dc.relation.ispartofComputational Problems of Electrical Engineering, 2 (12), 2022
dc.relation.references[1] C. O’Connor, “Chromosome mapping: Idiograms”. https://www.nature.com/scitable/topicpage/chromosome-mapping-idiograms-302/, 2008.
dc.relation.references[2] C. O’Connor, “Karyotyping for Chromosomal Abnormalities”. https://www.nature.com/scitable/topicpage/karyotyping-for-chromosomal-abnormalities-298/, 2008.
dc.relation.references[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.
dc.relation.references[4] O. Pysarchuk, Y. Mironov, “Decision support system for medical pathology recognition”, ScienceBased Technologies, vol. 49, no. 1, pp. 13–22, 2021 (Ukrainian).
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[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.
dc.relation.references[10] A. Buades, B. Coll, J. Morel, “Non-Local Means Denoising”, IPOL Journal, vol. 1, pp. 208–212, 2021.
dc.relation.references[11] “Median Filter”, https://en.wikipedia.org/wiki/Median_filter, Nov 21, 2022.
dc.relation.referencesen[1] C. O’Connor, "Chromosome mapping: Idiograms". https://www.nature.com/scitable/topicpage/chromosome-mapping-idiograms-302/, 2008.
dc.relation.referencesen[2] C. O’Connor, "Karyotyping for Chromosomal Abnormalities". https://www.nature.com/scitable/topicpage/karyotyping-for-chromosomal-abnormalities-298/, 2008.
dc.relation.referencesen[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.
dc.relation.referencesen[4] O. Pysarchuk, Y. Mironov, "Decision support system for medical pathology recognition", ScienceBased Technologies, vol. 49, no. 1, pp. 13–22, 2021 (Ukrainian).
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[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.
dc.relation.referencesen[10] A. Buades, B. Coll, J. Morel, "Non-Local Means Denoising", IPOL Journal, vol. 1, pp. 208–212, 2021.
dc.relation.referencesen[11] "Median Filter", https://en.wikipedia.org/wiki/Median_filter, Nov 21, 2022.
dc.relation.urihttps://www.nature.com/scitable/topicpage/chromosome-mapping-idiograms-302/
dc.relation.urihttps://www.nature.com/scitable/topicpage/karyotyping-for-chromosomal-abnormalities-298/
dc.relation.urihttps://en.wikipedia.org/wiki/Median_filter
dc.rights.holder© Національний університет “Львівська політехніка”, 2022
dc.subjectcomputer vision
dc.subjectfeature extraction
dc.subjectimage processing
dc.subjectnoise removal
dc.titleExtraction of Ideogram Features for Diagnosing Chromosomal Abnormalities
dc.title.alternativeВиділення ознак ідеограм для розпізнавання хромосомних аномалій
dc.typeArticle

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