Automatic alignment of stacks of filament data

V. J. Dercksen, B. Weber, D. Günther, M. Oberländer, S. Prohaska, H. Hege
{"title":"Automatic alignment of stacks of filament data","authors":"V. J. Dercksen, B. Weber, D. Günther, M. Oberländer, S. Prohaska, H. Hege","doi":"10.1109/ISBI.2009.5193216","DOIUrl":null,"url":null,"abstract":"We present a fast and robust method for the alignment of image stacks containing filamentous structures. Such stacks are usually obtained by physical sectioning a specimen, followed by an optical sectioning of each slice. For reconstruction, the filaments have to be traced and the sub-volumes aligned. Our algorithm takes traced filaments as input and matches their endpoints to find the optimal transform. We show that our method is able to quickly and accurately align sub-volumes containing neuronal processes, acquired using brightfield microscopy. Our method also makes it possible to align traced microtubuli, obtained from electron tomography data, which are extremely difficult to align manually.","PeriodicalId":272938,"journal":{"name":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ISBI.2009.5193216","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 17

Abstract

We present a fast and robust method for the alignment of image stacks containing filamentous structures. Such stacks are usually obtained by physical sectioning a specimen, followed by an optical sectioning of each slice. For reconstruction, the filaments have to be traced and the sub-volumes aligned. Our algorithm takes traced filaments as input and matches their endpoints to find the optimal transform. We show that our method is able to quickly and accurately align sub-volumes containing neuronal processes, acquired using brightfield microscopy. Our method also makes it possible to align traced microtubuli, obtained from electron tomography data, which are extremely difficult to align manually.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
自动校准的长丝数据堆栈
提出了一种快速、鲁棒的包含丝状结构的图像堆叠对齐方法。这种叠层通常是通过对标本进行物理切片,然后对每个切片进行光学切片来获得的。为了重建,细丝必须被追踪,子体量必须对齐。我们的算法以跟踪的细丝作为输入,匹配它们的端点来找到最优变换。我们表明,我们的方法能够快速准确地对齐包含神经元过程的子体积,使用明场显微镜获得。我们的方法还使从电子断层扫描数据中获得的追踪微管对齐成为可能,这些微管很难手动对齐。
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 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Automatic alignment of stacks of filament data Analysis of nerve activity and optical signals from mouse brain stem to identify cells generating respiratory rhythms Segmentation and classification of triple negative breast cancers using DCE-MRI Improved registration for large electron microscopy images Special purpose 3-D reconstruction and restoration algorithms for electron microscopy of nanoscale objects and an enabling software toolkit
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1