Rapid and fully automated blood vasculature analysis in 3D light-sheet image volumes of different or...
Rapid and fully automated blood vasculature analysis in 3D light-sheet image volumes of different organs
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Author / Creator
Spangenberg, Philippa , Hagemann, Nina , Squire, Anthony , Foerster, Nils , Krauss, Sascha D , Yachao Qi , Ayan Mohamud Yusuf , Wang, Jing , Grueneboom, Anika , Kowitz, Lennart , Korste, Sebastian , Totzeck, Matthias , Cibir, Zuelal , Ali Ata Tuz , Singh, Vikramjeet , Siemes, Devon , Struensee, Laura , Engel, Daniel R , Ludewig, Peter , Melo, Luiza Mn , Helfrich, Iris , Chen, Jianxu , Gunzer, Matthias , Hermann, Dirk M and Mosig, Axel
Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
Journal title
Language
English
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Publisher
Cold Spring Harbor: Cold Spring Harbor Laboratory Press
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Scope and Contents
Contents
Blood vasculature represents a complex network of vessels with varying lengths and diameters that are precisely organized in space to allow proper tissue function. Light-sheet fluorescence microscopy (LSFM) is very useful to generate tomograms of tissue vasculature with high spatial accuracy. Yet, quantitative LSFM analysis is still cumbersome and available methods are restricted to single organs and advanced computing hardware. Here, we introduce VesselExpress, an automated software that reliably analyzes six characteristic vascular network parameters including vessel diameter in LSFM data on average computing hardware. VesselExpress is ~100 times faster than other existing vessel analysis tools, requires no user interaction, integrates batch processing, and parallelization. Employing an innovative dual Frangi filter approach we show that obesity induces a large-scale modulation of brain vasculature in mice and that seven other major organs differ strongly in their 3D vascular makeup. Hence, VesselExpress transforms LSFM from an observational to an analytical working tool. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://zenodo.org/record/6025935#.YyGN5S0RqJ8...
Alternative Titles
Full title
Rapid and fully automated blood vasculature analysis in 3D light-sheet image volumes of different organs
Authors, Artists and Contributors
Author / Creator
Hagemann, Nina
Squire, Anthony
Foerster, Nils
Krauss, Sascha D
Yachao Qi
Ayan Mohamud Yusuf
Wang, Jing
Grueneboom, Anika
Kowitz, Lennart
Korste, Sebastian
Totzeck, Matthias
Cibir, Zuelal
Ali Ata Tuz
Singh, Vikramjeet
Siemes, Devon
Struensee, Laura
Engel, Daniel R
Ludewig, Peter
Melo, Luiza Mn
Helfrich, Iris
Chen, Jianxu
Gunzer, Matthias
Hermann, Dirk M
Mosig, Axel
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Primary Identifiers
Record Identifier
TN_cdi_proquest_journals_2715168770
Permalink
https://devfeature-collection.sl.nsw.gov.au/record/TN_cdi_proquest_journals_2715168770
Other Identifiers
E-ISSN
2692-8205
DOI
10.1101/2022.09.14.507895
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https://www.proquest.com/docview/2715168770?pq-origsite=primo&accountid=13902