Analysis of human chromosome images for the identification of centromere position and length
Automated chromosome classification is an essential task in cytogenetics. The genetic disorders and abnormalities that occur to the future generation can be predicted through analysing the various characteristics of the chromosomes. The chromosome classification is mainly based on geometric and morp...
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| creator | Loganathan, E. Anuja, M. R. Madian, N. |
| description | Automated chromosome classification is an essential task in cytogenetics. The genetic disorders and abnormalities that occur to the future generation can be predicted through analysing the various characteristics of the chromosomes. The chromosome classification is mainly based on geometric and morphological features. An effective algorithm for chromosome geometric feature extraction is presented. The geometric features of the chromosome are length and centromere. The morphological features are banding pattern. The paper deals with chromosome length and centromere position. The centromere plays an important role to determine the position of P Arm and Q Arm. The P Arm and Q Arm are calculated. The total length is calculated by the sum of P Arm and Q Arm. The proposed algorithm helps in calculating length by curve fitting method which is based on the skeletonization algorithm. The centromere position is identified by finding the concave and convex points on chromosome images. |
| doi_str_mv | 10.1109/PHT.2013.6461348 |
| format | Conference Proceeding |
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The proposed algorithm helps in calculating length by curve fitting method which is based on the skeletonization algorithm. 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The total length is calculated by the sum of P Arm and Q Arm. The proposed algorithm helps in calculating length by curve fitting method which is based on the skeletonization algorithm. The centromere position is identified by finding the concave and convex points on chromosome images.</description><subject>Abnormalities</subject><subject>Algorithms</subject><subject>Biological cells</subject><subject>Chromosomes</subject><subject>Classification</subject><subject>Classification algorithms</subject><subject>Concavity and Convexity</subject><subject>Curve fitting</subject><subject>Educational institutions</subject><subject>Genetics</subject><subject>Humans</subject><subject>Image segmentation</subject><subject>Mathematical analysis</subject><subject>Skeleton</subject><issn>2377-5262</issn><issn>2377-5270</issn><isbn>9781467327657</isbn><isbn>1467327654</isbn><isbn>9781467327664</isbn><isbn>1467327662</isbn><isbn>9781467327671</isbn><isbn>1467327670</isbn><fulltext>true</fulltext><rsrctype>conference_proceeding</rsrctype><creationdate>2013</creationdate><recordtype>conference_proceeding</recordtype><sourceid>6IE</sourceid><sourceid>RIE</sourceid><recordid>eNpVkM1LAzEQxeMXWGrvgpccvWxNskkmeyxFrVDQQ70JS5qdtJHdTd1sD_3vXW0RPA3z3m8evCHklrMp56x4eFuspoLxfKql5rk0Z2RSgOFSQy5Aa3lORiIHyJQAdvHPU3D552lxTSYpfTLGhlRtQI7Ix6y19SGFRKOn231jW-q2XWxiig3S0NgNJupjR_vtsFbY9sEHZ_sQ258LNwgDjR3SXUzhV7ZtRWtsN_32hlx5WyecnOaYvD89ruaLbPn6_DKfLbMgmOkzUFopZ12BQnDmtCkqrzQYURlYVxrVOndOO0BnIQf0XkltvVTcG1chynxM7o-5uy5-7TH1ZROSw7q2LcZ9Krnhqig0ABvQuyMaELHcdUPD7lCe3pp_AzSEaCc</recordid><startdate>201301</startdate><enddate>201301</enddate><creator>Loganathan, E.</creator><creator>Anuja, M. 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R. ; Madian, N.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-i208t-75655cac9e2210c689df56782d87bd6e5b3cc6c7eca737eff546af451f8cdee43</frbrgroupid><rsrctype>conference_proceedings</rsrctype><prefilter>conference_proceedings</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Abnormalities</topic><topic>Algorithms</topic><topic>Biological cells</topic><topic>Chromosomes</topic><topic>Classification</topic><topic>Classification algorithms</topic><topic>Concavity and Convexity</topic><topic>Curve fitting</topic><topic>Educational institutions</topic><topic>Genetics</topic><topic>Humans</topic><topic>Image segmentation</topic><topic>Mathematical analysis</topic><topic>Skeleton</topic><toplevel>online_resources</toplevel><creatorcontrib>Loganathan, E.</creatorcontrib><creatorcontrib>Anuja, M. R.</creatorcontrib><creatorcontrib>Madian, N.</creatorcontrib><collection>IEEE Electronic Library (IEL) Conference Proceedings</collection><collection>IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume</collection><collection>IEEE Xplore All Conference Proceedings</collection><collection>IEEE Electronic Library (IEL)</collection><collection>IEEE Proceedings Order Plans (POP All) 1998-Present</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Loganathan, E.</au><au>Anuja, M. R.</au><au>Madian, N.</au><format>book</format><genre>proceeding</genre><ristype>CONF</ristype><atitle>Analysis of human chromosome images for the identification of centromere position and length</atitle><btitle>2013 IEEE Point-Of-Care Healthcare Technologies</btitle><stitle>PHT</stitle><date>2013-01</date><risdate>2013</risdate><spage>314</spage><epage>317</epage><pages>314-317</pages><issn>2377-5262</issn><eissn>2377-5270</eissn><isbn>9781467327657</isbn><isbn>1467327654</isbn><eisbn>9781467327664</eisbn><eisbn>1467327662</eisbn><eisbn>9781467327671</eisbn><eisbn>1467327670</eisbn><abstract>Automated chromosome classification is an essential task in cytogenetics. The genetic disorders and abnormalities that occur to the future generation can be predicted through analysing the various characteristics of the chromosomes. The chromosome classification is mainly based on geometric and morphological features. An effective algorithm for chromosome geometric feature extraction is presented. The geometric features of the chromosome are length and centromere. The morphological features are banding pattern. The paper deals with chromosome length and centromere position. The centromere plays an important role to determine the position of P Arm and Q Arm. The P Arm and Q Arm are calculated. The total length is calculated by the sum of P Arm and Q Arm. The proposed algorithm helps in calculating length by curve fitting method which is based on the skeletonization algorithm. The centromere position is identified by finding the concave and convex points on chromosome images.</abstract><pub>IEEE</pub><doi>10.1109/PHT.2013.6461348</doi><tpages>4</tpages></addata></record> |
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| source | IEEE Electronic Library (IEL) Conference Proceedings |
| subjects | Abnormalities Algorithms Biological cells Chromosomes Classification Classification algorithms Concavity and Convexity Curve fitting Educational institutions Genetics Humans Image segmentation Mathematical analysis Skeleton |
| title | Analysis of human chromosome images for the identification of centromere position and length |
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