Automated cell segmentation in FIJI® using the DRAQ5 nuclear dye

BMC Bioinformatics

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[1] 0000 0001 1010 1663, grid.419547.a, Max Planck Institute for Polymer Research, Ackermannweg 10, 55128, Mainz, Germany;Institute of Pathology, Universitätsmedizin-Mainz, Langenbeckstraße 1, 55131, Mainz, Germany;

关键词: Cell segmentation;    Image processing;    Batch processing;    Fiji;    ImageJ;    DRAQ5;   

DOI  :  10.1186/s12859-019-2602-2

来源: publisher

【 摘 要 】

BackgroundImage segmentation and quantification are essential steps in quantitative cellular analysis. In this work, we present a fast, customizable, and unsupervised cell segmentation method that is based solely on Fiji (is just ImageJ)®, one of the most commonly used open-source software packages for microscopy analysis. In our method, the “leaky” fluorescence from the DNA stain DRAQ5 is used for automated nucleus detection and 2D cell segmentation.ResultsBased on an evaluation with HeLa cells compared to human counting, our algorithm reached accuracy levels above 92% and sensitivity levels of 94%. 86% of the evaluated cells were segmented correctly, and the average intersection over union score of detected segmentation frames to manually segmented cells was above 0.83. Using this approach, we quantified changes in the projected cell area, circularity, and aspect ratio of THP-1 cells differentiating from monocytes to macrophages, observing significant cell growth and a transition from circular to elongated form. In a second application, we quantified changes in the projected cell area of CHO cells upon lowering the incubation temperature, a common stimulus to increase protein production in biotechnology applications, and found a stark decrease in cell area.ConclusionsOur method is straightforward and easily applicable using our staining protocol. We believe this method will help other non-image processing specialists use microscopy for quantitative image analysis.

【 授权许可】

CC BY