Image analysis with Immuno Cytoplasm

This program enables the surface of the cytoplasmic staining to be calculated. After extraction of the nuclei, it also enables the number of cells presenting positive staining to be estimated and categorized according to their staining intensity.

The protocol :

The different stages of image analysis using the Immuno Cytoplasm algorithm are as follows :

  • Identification of the color plane
    The algorithm carries out automatic color deconvolution (DAB/H or AEC/H). This deconvolution can subsequentlybeadjusted by the user.
  • Image segmentation – Stage 1
    The image segmentation process enables identification of the objects that are to be analyzed. This process is carried out automatically and can subsequently be refined using a cursor.
  • Image segmentation – Stage 2 
    The second stage of segmentation involves isolating the non-stained nuclei from the cytoplasmic area to be analyzed.
  • Definition of staining positivity thresholds
    The segmentation of objects can be refined via morphomathematical processing. The thresholds of the four categories of staining intensity are defined.
  • Definition of measuring parameters
    After isolation of the nuclei, the mean nuclear surface can then be determined.

Results present the number of estimated nuclei as well as the percentage of the positive staining surface. This enables the number of positive cells to be estimated.

Objects are categorized according to the average intensity of their staining and sorted into 4 predetermined categories from negative to intensity levels 0, 1+, 2+ and 3+. The proportion of the positive cytoplasmic surface relating to the entire cytoplasmic area, which is the ratio of the stained area against the total area, then determines the staining index.

Results also indicate the proportion of cells for each of the four staining categories. The proportion of stained cells then corresponds to the percentage of nuclei present in the cells that are positive during staining.