Keywords
cell nuclei
DNA image cytometry
fluorescense
genome size
image segmentation
ImageJ
ploidy
plants
How to Cite
Abstract
The article presents the development of BioDecod, a tool for the automated detection and quantification of cell nuclei in images. BioDecod enables accurate nuclei identification and counting, measurement of their fluorescence intensity, and generation of structured data. This Windows-based application developed in TypeScript has user-friendly interface and a minimal number of adjustable parameters. In comparison with ImageJ and CellProfiler, BioDecod simplifies the analysis workflow by allowing users to work within a single window, visualize changes in real-time, and process up to 100 images simultaneously. The analysis algorithm involves image segmentation via adaptive thresholding to identify nuclei, size-based filtering, and calculation of integral fluorescence parameters across four channels, with subsequent data export to Excel. Data visualization is implemented through scatter plots and histograms, featuring functionality for population gating and automatic statistical calculations. A comparative analysis of BioDecod and ImageJ demonstrated the superior efficiency of BioDecod in image processing, evidenced by a lower coefficient of variation (CV) – 6.31–7.69 % versus 14.26–31.1 %. This improvement is attributed to BioDecod’s effective filtering of particle populations to exclude artifacts and image overlaps. BioDecod was validated using real-world samples – plants with genome sizes ranging from 0.45 to 64.54 pg. In summary, BioDecod provides a comprehensive solution for the acquisition and analysis of cell nucleus images, combining ease of use, configurable flexibility, and measurement precision, which makes it a valuable tool for researchers in the field of image cytometry.
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