{"title":"cDNA微阵列图像的无参数自动斑点检测方法","authors":"Iman Rezaeian, L. Rueda","doi":"10.1109/BIBM.2010.5706596","DOIUrl":null,"url":null,"abstract":"Gridding cDNA microarray images is a critical step in gene expression analysis, since any errors in this stage are propagated in future steps in the analysis. We propose a fully automatic approach to detect the locations of the spots. The approach first detects and corrects rotations in the sub-grids by an affine transformation, followed by a polynomial-time optimal multi-level thresholding algorithm that finds the positions of the spots. Additionally, a new validity index is proposed in order to find the correct number of spots in each sub-grid, followed by a refinement procedure used to improve the performance of the method. Extensive experiments on real-life microarray images show that the proposed method performs these tasks automatically and with very high accuracy.","PeriodicalId":275098,"journal":{"name":"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"A parameterless automatic spot detection method for cDNA microarray images\",\"authors\":\"Iman Rezaeian, L. Rueda\",\"doi\":\"10.1109/BIBM.2010.5706596\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Gridding cDNA microarray images is a critical step in gene expression analysis, since any errors in this stage are propagated in future steps in the analysis. We propose a fully automatic approach to detect the locations of the spots. The approach first detects and corrects rotations in the sub-grids by an affine transformation, followed by a polynomial-time optimal multi-level thresholding algorithm that finds the positions of the spots. Additionally, a new validity index is proposed in order to find the correct number of spots in each sub-grid, followed by a refinement procedure used to improve the performance of the method. Extensive experiments on real-life microarray images show that the proposed method performs these tasks automatically and with very high accuracy.\",\"PeriodicalId\":275098,\"journal\":{\"name\":\"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"volume\":\"64 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2010.5706596\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2010.5706596","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A parameterless automatic spot detection method for cDNA microarray images
Gridding cDNA microarray images is a critical step in gene expression analysis, since any errors in this stage are propagated in future steps in the analysis. We propose a fully automatic approach to detect the locations of the spots. The approach first detects and corrects rotations in the sub-grids by an affine transformation, followed by a polynomial-time optimal multi-level thresholding algorithm that finds the positions of the spots. Additionally, a new validity index is proposed in order to find the correct number of spots in each sub-grid, followed by a refinement procedure used to improve the performance of the method. Extensive experiments on real-life microarray images show that the proposed method performs these tasks automatically and with very high accuracy.