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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.
Introduction: Older patients with multimorbidity, polypharmacy and related complex care needs represent a growing proportion of the population and a challenge for healthcare systems. Particularly in transitional care (hospital admission and hospital discharge), medical errors, inappropriate treatment, patient concerns and lack of confidence in healthcare are major problems that may arise from a lack of information continuity. The aim of this study is to develop an intervention to improve informational continuity of care at the interface between general practice and hospital care.
Methods and analysis: A qualitative approach will be used to develop our participatory intervention. Overall, 32 semistructured interviews with relevant stakeholders will be conducted and analysed. The stakeholders will include healthcare professionals from the outpatient setting (general practitioners, healthcare assistants, ambulatory care nurses) and the inpatient setting (clinical doctors, nurses, pharmacists, clinical information scientists) as well as patients and informal caregivers. At a series of workshops based on the results of the stakeholder analyses, we aim to develop a participatory intervention that will then be implemented in a subsequent pilot study. The same stakeholder groups will be invited for participation in the workshops.
Ethics and dissemination: Ethical approval for this study was waived by the Ethics Committee of Goethe University Frankfurt because of the nature of the proposed study. Written informed consent will be obtained from all study participants prior to participation. Results will be tested in a pilot study and disseminated at (inter)national conferences and via publication in peer-reviewed journals.