Fig. 2: Image segmentation and histo-cytometric quantification of 3D static images using Cecelia. | Nature Communications

Fig. 2: Image segmentation and histo-cytometric quantification of 3D static images using Cecelia.

From: Cecelia: a multifunctional image analysis toolbox for decoding spatial cellular interactions and behaviour

Fig. 2

a Example confocal image containing diverse cell shapes and sizes and labels that cannot be segmented using current workflows. This 3D image contains 8 fluorescent channels (designated by the coloured circles). Cecelia’s principle is to combine a mix of segmentations for combined spatial analysis. b Confocal imaging of mouse spleen 1.5 days after LCMV infection. Individual and merged segmentation of the individual markers is shown. c Histo-cytometry plots of merged image segmentation to identify cell types. d Spatial analysis and quantification of cellular interactions between virus specific CD8+ T cells, XCR1+ DCs and virus infected cells in mouse spleen 1.5 days after LCMV infection (n = 6, 2 independent experiments with 3 mice, two-sided t-test). Source data are provided as a Source Data file.

Back to article page