PT  - JOURNAL ARTICLE
AU  - Sébastien Herbert
AU  - Léo Valon
AU  - Laure Mancini
AU  - Nicolas Dray
AU  - Paolo Caldarelli
AU  - Jérôme Gros
AU  - Elric Esposito
AU  - Spencer L. Shorte
AU  - Laure Bally-Cuif
AU  - Romain Levayer
AU  - Nathalie Aulner
AU  - Jean-Yves Tinevez
TI  - DProj: A toolbox for local 2D projection and accurate morphometrics of large 3D microscopy images
AID  - 10.1101/2021.01.15.426809
DP  - 2021 Jan 01
TA  - bioRxiv
PG  - 2021.01.15.426809
4099  - http://biorxiv.org/content/early/2021/01/18/2021.01.15.426809.short
4100  - http://biorxiv.org/content/early/2021/01/18/2021.01.15.426809.full
AB  - Background Quantitative imaging of epithelial tissues prompts for bioimage analysis tools that are widely applicable and accurate. In the case of imaging 3D tissues, a common post-processing step consists in projecting the acquired 3D volume on a 2D plane mapping the tissue surface. Indeed, while segmenting the tissue cells is amenable on 2D projections, it is still very difficult and cumbersome in 3D. However, for many specimen and models used in Developmental and Cell Biology, the complex content of the image volume surrounding the epithelium in a tissue often reduces the visibility of the biological object in the projection, compromising its subsequent analysis. In addition, the projection will distort the geometry of the tissue and can lead to strong artifacts in the morphology measurement.Results Here we introduce DProj a user-friendly tool-box built to robustly project epithelia on their 2D surface from 3D volumes, and to produce accurate morphology measurement corrected for the projection distortion, even for very curved tissues. DProj is built upon two components. LocalZProjector is a user-friendly and configurable Fiji plugin that generates 2D projections and height-maps from potentially large 3D stacks (larger than 40 GB per time-point) by only incorporating the signal of interest, despite a possibly complex image content. DeProj is a MATLAB tool that generates correct morphology measurements by combining the height-map output (such as the one offered by LocalZProjector) and the results of the cell segmentation on the 2D projection. In this paper we demonstrate DProj effectiveness over a wide range of different biological samples. We then compare its performance and accuracy against similar existing tools.Conclusions We find that LocalZProjector performs well even in situations where the volume to project contains spurious structures. We show that it can process large images without a pre-processing step. We study the impact of geometrical distortions on morphological measurements induced by the projection. We measured very large distortions which are then corrected by DeProj, providing accurate outputs.Competing Interest StatementThe authors have declared no competing interest.