{"title":"延时显微镜下祖细胞的定量和分割","authors":"R. Suresh, N. Jayalakshmi","doi":"10.1145/1722024.1722071","DOIUrl":null,"url":null,"abstract":"The analysis of progenitor cell proliferation in image sequences helps in understanding the formation of organ, identifying reason for decease and cell based therapies. We introduce a technique using morphological techniques for cell segmentation and extended h-maxima transformation for finding position of the cell in the frame. The over segmentation problem of watershed algorithms is reduced by morphologic erosion, allowing for more accurate quantification, even in low contrast images. The number of cells and the average cell size could be determined in the image. Application of this method to a difficult dataset allowed us to identify 96% of the cells in the image.","PeriodicalId":39379,"journal":{"name":"In Silico Biology","volume":"1 1","pages":"40"},"PeriodicalIF":0.0000,"publicationDate":"2010-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1145/1722024.1722071","citationCount":"3","resultStr":"{\"title\":\"Quantification and segmentation of progenitor cells in time-lapse microscopy\",\"authors\":\"R. Suresh, N. Jayalakshmi\",\"doi\":\"10.1145/1722024.1722071\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The analysis of progenitor cell proliferation in image sequences helps in understanding the formation of organ, identifying reason for decease and cell based therapies. We introduce a technique using morphological techniques for cell segmentation and extended h-maxima transformation for finding position of the cell in the frame. The over segmentation problem of watershed algorithms is reduced by morphologic erosion, allowing for more accurate quantification, even in low contrast images. The number of cells and the average cell size could be determined in the image. Application of this method to a difficult dataset allowed us to identify 96% of the cells in the image.\",\"PeriodicalId\":39379,\"journal\":{\"name\":\"In Silico Biology\",\"volume\":\"1 1\",\"pages\":\"40\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-02-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1145/1722024.1722071\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"In Silico Biology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/1722024.1722071\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"Medicine\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"In Silico Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/1722024.1722071","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"Medicine","Score":null,"Total":0}
Quantification and segmentation of progenitor cells in time-lapse microscopy
The analysis of progenitor cell proliferation in image sequences helps in understanding the formation of organ, identifying reason for decease and cell based therapies. We introduce a technique using morphological techniques for cell segmentation and extended h-maxima transformation for finding position of the cell in the frame. The over segmentation problem of watershed algorithms is reduced by morphologic erosion, allowing for more accurate quantification, even in low contrast images. The number of cells and the average cell size could be determined in the image. Application of this method to a difficult dataset allowed us to identify 96% of the cells in the image.
In Silico BiologyComputer Science-Computational Theory and Mathematics
CiteScore
2.20
自引率
0.00%
发文量
1
期刊介绍:
The considerable "algorithmic complexity" of biological systems requires a huge amount of detailed information for their complete description. Although far from being complete, the overwhelming quantity of small pieces of information gathered for all kind of biological systems at the molecular and cellular level requires computational tools to be adequately stored and interpreted. Interpretation of data means to abstract them as much as allowed to provide a systematic, an integrative view of biology. Most of the presently available scientific journals focus either on accumulating more data from elaborate experimental approaches, or on presenting new algorithms for the interpretation of these data. Both approaches are meritorious.