An image analysis tool for cell migration assay with a large sample size

Di Yin, Hongbo Zhang, Shih-Mo Yang, R. Yin, Wenjun Zhang
{"title":"An image analysis tool for cell migration assay with a large sample size","authors":"Di Yin, Hongbo Zhang, Shih-Mo Yang, R. Yin, Wenjun Zhang","doi":"10.1117/12.2667479","DOIUrl":null,"url":null,"abstract":"Cell migration assay is the most common research approach for cell migration. Quantitative research and analysis are carried out by measuring the migration of cells into the region that is artificially created among confluent monolayer cells. To improve the efficiency and accuracy of the analysis, the software/tools were developed to assist the image analysis process. However, these software and tools are still at the stage of measuring a single sample, which cannot satisfy the requirement of large sample size for cell migration assay device. In this paper, an image analysis tool based on Fiji is developed, which can segment multiple samples from a scanned image and then analyze a single sample in batch. In addition, the screening function should be added for the application scenario of large sample size. The samples can be filtered according to different conditions to improve the consistency of experimental conditions. The results show that the developed analysis tool ATCA has high accuracy in identifying cell-free zones, with a difference of 2.3% from the tool WHST and 2.9% from manual operation. The analysis efficiency of this tool is 15 times that of manual operation.","PeriodicalId":345723,"journal":{"name":"Fifth International Conference on Computer Information Science and Artificial Intelligence","volume":"70 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Fifth International Conference on Computer Information Science and Artificial Intelligence","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1117/12.2667479","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

Cell migration assay is the most common research approach for cell migration. Quantitative research and analysis are carried out by measuring the migration of cells into the region that is artificially created among confluent monolayer cells. To improve the efficiency and accuracy of the analysis, the software/tools were developed to assist the image analysis process. However, these software and tools are still at the stage of measuring a single sample, which cannot satisfy the requirement of large sample size for cell migration assay device. In this paper, an image analysis tool based on Fiji is developed, which can segment multiple samples from a scanned image and then analyze a single sample in batch. In addition, the screening function should be added for the application scenario of large sample size. The samples can be filtered according to different conditions to improve the consistency of experimental conditions. The results show that the developed analysis tool ATCA has high accuracy in identifying cell-free zones, with a difference of 2.3% from the tool WHST and 2.9% from manual operation. The analysis efficiency of this tool is 15 times that of manual operation.
用于大样本量细胞迁移试验的图像分析工具
细胞迁移试验是研究细胞迁移最常用的方法。定量研究和分析是通过测量细胞迁移到在融合单层细胞之间人工创建的区域来进行的。为了提高分析的效率和准确性,开发了软件/工具来辅助图像分析过程。然而,这些软件和工具还停留在单个样品的测量阶段,无法满足细胞迁移测定装置大样本量的要求。本文开发了一种基于斐济的图像分析工具,可以从扫描图像中分割出多个样本,然后批量分析单个样本。此外,对于大样本量的应用场景,应增加筛选功能。可根据不同条件对样品进行过滤,提高实验条件的一致性。结果表明,开发的分析工具ATCA在识别细胞无区方面具有较高的准确性,与工具WHST相差2.3%,与人工操作相差2.9%。该工具的分析效率是人工操作的15倍。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
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