QuickPIV: efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis
The technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions,...
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| Main Authors: | , , , , , |
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| Format: | Article (Journal) |
| Language: | English |
| Published: |
04 December 2021
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| In: |
BMC bioinformatics
Year: 2021, Volume: 22, Pages: 1-20 |
| ISSN: | 1471-2105 |
| DOI: | 10.1186/s12859-021-04474-0 |
| Online Access: | Verlag, lizenzpflichtig, Volltext: https://doi.org/10.1186/s12859-021-04474-0
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| Author Notes: | Marc Pereyra, Armin Drusko, Franziska Krämer, Frederic Strobl, Ernst H. K. Stelzer and Franziska Matthäus |
| Summary: | The technical development of imaging techniques in life sciences has enabled the three-dimensional recording of living samples at increasing temporal resolutions. Dynamic 3D data sets of developing organisms allow for time-resolved quantitative analyses of morphogenetic changes in three dimensions, but require efficient and automatable analysis pipelines to tackle the resulting Terabytes of image data. Particle image velocimetry (PIV) is a robust and segmentation-free technique that is suitable for quantifying collective cellular migration on data sets with different labeling schemes. This paper presents the implementation of an efficient 3D PIV package using the Julia programming language—quickPIV. Our software is focused on optimizing CPU performance and ensuring the robustness of the PIV analyses on biological data. |
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| Item Description: | Gesehen am 21.12.2021 |
| Physical Description: | Online Resource |
| ISSN: | 1471-2105 |
| DOI: | 10.1186/s12859-021-04474-0 |