延时显微镜下祖细胞的定量和分割

Q2 Medicine
R. Suresh, N. Jayalakshmi
{"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":null,"pages":null},"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\":null,\"pages\":null},\"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}
引用次数: 3

摘要

对图像序列中祖细胞增殖的分析有助于了解器官的形成,确定疾病的原因和基于细胞的治疗。我们介绍了一种使用形态学技术进行细胞分割和扩展h-maxima变换来寻找细胞在帧中的位置的技术。分水岭算法的过度分割问题通过形态侵蚀减少,允许更准确的量化,即使在低对比度的图像。在图像中可以确定细胞的数量和平均细胞大小。将这种方法应用于一个困难的数据集,使我们能够识别图像中96%的细胞。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
In Silico Biology
In Silico Biology Computer 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.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信