QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis

Abstract 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 i...

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Autores principales:	Marc Pereyra, Armin Drusko, Franziska Krämer, Frederic Strobl, Ernst H. K. Stelzer, Franziska Matthäus
Formato:	article
Lenguaje:	EN
Publicado:	BMC 2021
Materias:	Particle image velocimetry Light-sheet fluorescence microscopy Collective cell migration Julia 3D image analysis Tribolium castaneum Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/92145313d37c49e6b5ba523e1166c2cc
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spelling	oai:doaj.org-article:92145313d37c49e6b5ba523e1166c2cc2021-12-05T12:08:39ZQuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis10.1186/s12859-021-04474-01471-2105https://doaj.org/article/92145313d37c49e6b5ba523e1166c2cc2021-12-01T00:00:00Zhttps://doi.org/10.1186/s12859-021-04474-0https://doaj.org/toc/1471-2105Abstract 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.Marc PereyraArmin DruskoFranziska KrämerFrederic StroblErnst H. K. StelzerFranziska MatthäusBMCarticleParticle image velocimetryLight-sheet fluorescence microscopyCollective cell migrationJulia3D image analysisTribolium castaneumComputer applications to medicine. Medical informaticsR858-859.7Biology (General)QH301-705.5ENBMC Bioinformatics, Vol 22, Iss 1, Pp 1-20 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Particle image velocimetry Light-sheet fluorescence microscopy Collective cell migration Julia 3D image analysis Tribolium castaneum Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5
spellingShingle	Particle image velocimetry Light-sheet fluorescence microscopy Collective cell migration Julia 3D image analysis Tribolium castaneum Computer applications to medicine. Medical informatics R858-859.7 Biology (General) QH301-705.5 Marc Pereyra Armin Drusko Franziska Krämer Frederic Strobl Ernst H. K. Stelzer Franziska Matthäus QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis
description	Abstract 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	article
author	Marc Pereyra Armin Drusko Franziska Krämer Frederic Strobl Ernst H. K. Stelzer Franziska Matthäus
author_facet	Marc Pereyra Armin Drusko Franziska Krämer Frederic Strobl Ernst H. K. Stelzer Franziska Matthäus
author_sort	Marc Pereyra
title	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_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_sort	quickpiv: efficient 3d particle image velocimetry software applied to quantifying cellular migration during embryogenesis
publisher	BMC
publishDate	2021
url	https://doaj.org/article/92145313d37c49e6b5ba523e1166c2cc
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QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis

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