Image Analysis examples

Example 1 – positive cell percents

In this example blue (DAPI nuclear staining) as well as green fluorescence (immunostaining of an interest membrane protein) images were provided. The task was to count positive and negative cells, report the numbers and percent positivity, and provide images highlighting the decision process .

Merged channels image (Blue: nuclei, Green: membrane protein)
Identified positive / negative cells

Example 2 – surface versus depth of a 3d structure assayed from 2D sections

In this example, brightfield images and DAPI nuclear staining images were provided. The goal was to count cells on the surface and the cells inside the construct from which the sections were cut.

Bright Field microscopy image
Nuclei (DAPI staining)
Merged channels: surface cells indicated in blue, cells inside the construct indicated in cyan

Example 3 – Scratch assay – identify medium width of region

Here, scratch assay images were analysed. The automatic measurements involved first delineating the scratch area and then the identification of the slope for correcting non-vertical regions. The result is the corrected mean width of the scratch area.

Scratch assay brightfield image
Identified area and slope used for mean width determination

Example 4 – Actin filaments orientation

This example analyses actin fiber orientation in cells as result of external mechanical stimulation. The actin fibers were identified in ImageJ, all line segments coordonates were saved in a separate file and data were then analysed in Python to obtain histograms summarizing the orientations of all identified actin fibers.

original actin immunofluorescene image
identified actin fibers
Histogram showing the lenght of actin fibers on each direction of the plane