To produce a cellular image analysis, cell segmentation, a labeling process of each cell, is an essential and necessary step. Fluofarma’s image analysis tools are able to process several techniques of staining — immunofluorescence (IF) or immunohistochemistry (IHC) — applied on different biological materials (cells, tissue sections, TMA …).

Using segmentation information, different measures can be computed such as Intensity or Counting. A cell classification can also be achieved using custom features that characterize subcellular objects inside nuclei or cytoplasm.
Fluofarma’s solutions are also able to manage the particular case of neuronal cells. Pertinent features linked to neuronal biology can be extracted and proposed according to the needs of the client study.


Texture analysis methods provide high level features that allow a robust and a precise description of an image.
These tools are routinely exploited in biology for tissue segmentation and are very useful whatever the application domain (oncology, inflammation).

For instance, two examples of image segmentation, for Regions Of Interest (ROI) detection, are presented here below:

     > Detection of macro-structures inside colon images acquired using colon TMA in which each core was analyzed individually

     > Detection of the fibrotic area to provide a fibrotic percentage inside lung tissue sections

Based on the labeling of the different regions inside an image, it will thus possible to extract information thereby describing the image content: ROI percentage, custom indices to help a pathologist in his diagnostic, tissue structures description.