Wide-Range Segmentation of Cotyledon Epidermal Cells for Morphometrical Analysis and Mechanical Simulation

Cell segmentation from microscopic images is conventionally used to investigate cell morphology. However, the time expense for manual segmentation becomes extreme with increasing numbers of cells to be analyzed. Recent progress in automated image analysis techniques can facilitate efficient and accurate cell segmentation in wide-range confocal images. Pavement cells, which mainly comprise the epidermal tissue of plant leaves, show jigsaw puzzle-like shapes and provide a model for elucidating the mechanisms underlying the complex morphology of plant cells. This mini-review demonstrates the effectiveness of using a confocal image processing pipeline for morphometric analysis and mechanical simulation using Arabidopsis thaliana cotyledon pavement cells as an example. We examined A. thaliana cotyledon surfaces using wide-range confocal images and used an image processing pipeline in ImageJ software to extract epidermal cell contours. We then used the segmented epidermal cell images to provide examples of how this information can be used for morphometry and mechanical simulation. The use of this high-throughput segmentation method is not limited to plant epidermal tissue and can be applied to various biological materials. Therefore, our approach to microscopic image analysis will hopefully contribute to the advancement of quantitative cell morphology research.

Automated summary

Automated image analysis techniques have made cell segmentation from wide-range confocal images efficient and accurate, using Arabidopsis thaliana cotyledon pavement cells as an example. This high-throughput segmentation method can be applied to various biological materials, contributing to the advancement of quantitative cell morphology research.