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QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis
BACKGROUND: 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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642913/ https://www.ncbi.nlm.nih.gov/pubmed/34863116 http://dx.doi.org/10.1186/s12859-021-04474-0 |
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author | Pereyra, Marc Drusko, Armin Krämer, Franziska Strobl, Frederic Stelzer, Ernst H. K. Matthäus, Franziska |
author_facet | Pereyra, Marc Drusko, Armin Krämer, Franziska Strobl, Frederic Stelzer, Ernst H. K. Matthäus, Franziska |
author_sort | Pereyra, Marc |
collection | PubMed |
description | BACKGROUND: 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. RESULTS: QuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data. CONCLUSIONS: The presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview. |
format | Online Article Text |
id | pubmed-8642913 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-86429132021-12-06 QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis Pereyra, Marc Drusko, Armin Krämer, Franziska Strobl, Frederic Stelzer, Ernst H. K. Matthäus, Franziska BMC Bioinformatics Software BACKGROUND: 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. RESULTS: QuickPIV is three times faster than the Python implementation hosted in openPIV, both in 2D and 3D. Our software is also faster than the fastest 2D PIV package in openPIV, written in C++. The accuracy evaluation of our software on synthetic data agrees with the expected accuracies described in the literature. Additionally, by applying quickPIV to three data sets of the embryogenesis of Tribolium castaneum, we obtained vector fields that recapitulate the migration movements of gastrulation, both in nuclear and actin-labeled embryos. We show normalized squared error cross-correlation to be especially accurate in detecting translations in non-segmentable biological image data. CONCLUSIONS: The presented software addresses the need for a fast and open-source 3D PIV package in biological research. Currently, quickPIV offers efficient 2D and 3D PIV analyses featuring zero-normalized and normalized squared error cross-correlations, sub-pixel/voxel approximation, and multi-pass. Post-processing options include filtering and averaging of the resulting vector fields, extraction of velocity, divergence and collectiveness maps, simulation of pseudo-trajectories, and unit conversion. In addition, our software includes functions to visualize the 3D vector fields in Paraview. BioMed Central 2021-12-04 /pmc/articles/PMC8642913/ /pubmed/34863116 http://dx.doi.org/10.1186/s12859-021-04474-0 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Software Pereyra, Marc Drusko, Armin Krämer, Franziska Strobl, Frederic Stelzer, Ernst H. K. Matthäus, Franziska QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis |
title | QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis |
title_full | QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis |
title_fullStr | QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis |
title_full_unstemmed | QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis |
title_short | QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis |
title_sort | quickpiv: efficient 3d particle image velocimetry software applied to quantifying cellular migration during embryogenesis |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8642913/ https://www.ncbi.nlm.nih.gov/pubmed/34863116 http://dx.doi.org/10.1186/s12859-021-04474-0 |
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