{"title":"PIXEL SENSIBLE LOCAL BAND ANALYSIS IN MICROSCOPIC CHROMOSOME IMAGES USING CSPA.","authors":"D Somasundaram","doi":"","DOIUrl":null,"url":null,"abstract":"<p><p>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%.</p>","PeriodicalId":23230,"journal":{"name":"TSitologiia i genetika","volume":"50 1","pages":"52-6"},"PeriodicalIF":0.0000,"publicationDate":"2016-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"TSitologiia i genetika","FirstCategoryId":"1085","ListUrlMain":"","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
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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