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ImageJ SurfCut: a user-friendly pipeline for high-throughput extraction of cell contours from 3D image stacks.

BMC biology · 9 May 2019 · 10.1186/s12915-019-0657-1

Abstract

Background Many methods have been developed to quantify cell shape in 2D in tissues. For instance, the analysis of epithelial cells in Drosophila embryogenesis or jigsaw puzzle-shaped pavement cells in plant epidermis has led to the development of numerous quantification methods that are applied to 2D images. However, proper extraction of 2D cell contours from 3D confocal stacks for such analysis can be problematic. Results We developed a macro in ImageJ, SurfCut, with the goal to provide a user-friendly pipeline specifically designed to extract epidermal cell contour signals, segment cells in 2D and analyze cell shape. As a reference point, we compared our output to that obtained with MorphoGraphX (MGX). While both methods differ in the approach used to extract the layer of signal, they output comparable results for tissues with shallow curvature, such as pavement cell shape in cotyledon epidermis (as quantified with PaCeQuant). SurfCut was however not appropriate for cell or tissue samples with high curvature, as evidenced by a significant bias in shape and area quantification. Conclusion We provide a new ImageJ pipeline, SurfCut, that allows the extraction of cell contours from 3D confocal stacks. SurfCut and MGX have complementary advantages: MGX is well suited for curvy samples and more complex analyses, up to computational cell-based modeling on real templates; SurfCut is well suited for rather flat samples, is simple to use, and has the advantage to be easily automated for batch analysis of images in ImageJ. The combination of these two methods thus provides an ideal suite of tools for cell contour extraction in most biological samples, whether 3D precision or high-throughput analysis is the main priority.

Plant phenotyping relevance

植物表皮細胞の輪郭・形状を3D画像から抽出・定量するImageJパイプラインの開発と比較検証が中心であり、植物形態フェノタイピング手法に該当する。

abstractWe developed a macro in ImageJ, SurfCut, with the goal to provide a user-friendly pipeline specifically designed to extract epidermal cell contour signals, segment cells in 2D and analyze cell shape.
abstractSurfCut and MGX have complementary advantages: MGX is well suited for curvy samples and more complex analyses, up to computational cell-based modeling on real templates; SurfCut is well suited for rather flat samples, is simple to use, and has the advantage to be easily automated for batch analysis of images in ImageJ.

Code and data availability

The paper's authors publicly released both the SurfCut analysis macro (GitHub and Zenodo DOI 10.5281/zenodo.2635737) and the confocal microscopy dataset of plant samples used for the phenotyping measurements (Zenodo DOI 10.5281/zenodo.2577053).

Codepublic

Devo” and ERASMUS grant (20016-1-TR01-KA103-026029). Availability of data and materials The datasets generated and analyzed in this study are available in the Zenodo repository ( https://zenodo.org /), DOI:10.5281/zenodo.2577053 [ 34 ]. The script of the SurfCut macro and a more detailed step-by-step user guide are available at https://github.com/sverger/SurfCut [ 35 ], Zenodo DOI:10.5281/zenodo.2635737 [ 28 ]. Authors’ contributions OE, ML, and SV performed the experiments. SV wrote the ImageJ script “SurfCut.” OE analyzed the results. OE, ML, OH, and SV wrote the article. OH secured funding for this project. All authors read and approved the final manuscript. Ethics approval and cons

Open resource ↗sverger/SurfCut · lines:84-107
Datasetpublic

The datasets generated and analyzed in this study are available in the Zenodo repository ( https://zenodo.org /), DOI:10.5281/zenodo.2577053 [ 34 ].

Open resource ↗Zenodo · 10.5281/zenodo.2577053 · lines:84-107

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