TY  - JOUR
A1  - Pereyra, Marc
A1  - Drusko, Armin
A1  - Krämer, Franziska
A1  - Strobl, Frederic
A1  - Stelzer, Ernst H. K.
A1  - Matthäus, Franziska
T1  - QuickPIV: Efficient 3D particle image velocimetry software applied to quantifying cellular migration during embryogenesis
T2  - BMC bioinformatics
N2  - 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.
KW  - Particle image velocimetry
KW  - Light-sheet fluorescence microscopy
KW  - Collective cell migration
KW  - Julia
KW  - 3D image analysis
KW  - Tribolium castaneum
Y1  - 2021
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/69779
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-697793
SN  - 1471-2105
N1  - The Creative Commons Public Domain Dedication waiver (http://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.
N1  - Open Access funding enabled and organized by Projekt DEAL.
N1  - The data sets used and/or analyzed during the current study can be accessed through the following Zenodo https://doi.org/10.5281/zenodo.5504076.
N1  - Additional file 1. This file contains a video animating the rotation and slicing of the three-dimensional distribution of the maximum peak heights at each interrogation area during the PIV analysis using NSQECC of two 3D volumes of data set (i). Available through: https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-021-04474-0
VL  - 22
IS  - art. 579
SP  - 1
EP  - 20
PB  - Springer ; BioMed Central
CY  - Berlin ; Heidelberg ; London
ER  -