A1 Refereed original research article in a scientific journal
Fast4DReg – fast registration of 4D microscopy datasets
Authors: Pylvänäinen Joanna W., Laine Romain F., Saraiva Bruno M.S., Ghimire Sujan, Follain Gautier, Henriques Ricardo, Jacquemet Guillaume
Publisher: COMPANY BIOLOGISTS LTD
Publication year: 2023
Journal: Journal of Cell Science
Journal name in source: JOURNAL OF CELL SCIENCE
Journal acronym: J CELL SCI
Article number: jcs260728
Volume: 136
Issue: 4
Number of pages: 11
ISSN: 0021-9533
eISSN: 1477-9137
DOI: https://doi.org/10.1242/jcs.260728(external)
Web address : http://dx.doi.org/10.1242%2Fjcs.260728(external)
Self-archived copy’s web address: https://research.utu.fi/converis/portal/detail/Publication/179476567(external)
Unwanted sample drift is a common issue that plagues microscopy experiments, preventing accurate temporal visualization and quantification of biological processes. Although multiple methods and tools exist to correct images post acquisition, performing drift correction of three-dimensional (3D) videos using open-source solutions remains challenging and time consuming. Here, we present a new tool developed for ImageJ or Fiji called Fast4DReg that can quickly correct axial and lateral drift in 3D video-microscopy datasets. Fast4DReg works by creating intensity projections along multiple axes and estimating the drift between frames using two-dimensional cross-correlations. Using synthetic and acquired datasets, we demonstrate that Fast4DReg can perform better than other state-of-the-art open-source drift-correction tools and significantly outperforms them in speed. We also demonstrate that Fast4DReg can be used to register misaligned channels in 3D using either calibration slides or misaligned images directly. Altogether, Fast4DReg provides a quick and easy-to-use method to correct 3D imaging data before further visualization and analysis.
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