IF Granuloma
Detect granulomas using nuclear structure analysis and IF markers (e.g. CD11c, CD68), measure granuloma number, area, and density, and export up to 20 intensity, statistic, and morphometric parameters per cell compartment.
dentritic cells, macrophages, inflammation, granulomas, mouse, liver, fluorescence, microeinvironment, immune cells
The IF Granuloma App detects granulomas based on nuclear structure analysis and an adequate IF staining (e.g. CD11c, CD68). The number and area of Granulomas as well as their density is measured. Each segmented cell compartment is measured for up to 20 intensity, statistic and morphometric parameters.
Original image
Nuclei detection
Granuloma detection
Granuloma detection and phenotyping
Webinar
21 Oct, 2025
Multimodal Imaging of Cellular Senescence: Tissue Cytometry and Beyond
Blog Post
17 May, 2023
An Intro to Deep Learning in Biomedical Imaging
We support the following file formats:
- TissueFAXS (aqproj)
- StrataFAXS II (vmic)
- PreciPoint (vmic, gtif)
- Generic BigTIFF Import
- Support for multipage BigTIFF files
- OME-TIFF
- JPEG, PNG, BMP, TIFF
- Zeiss (czi)
- Hamamatsu NanoZoomer (ndpi)
- Aperio (svs)
- Leica (scn)
- 3D HISTECH Pannoramic
- Mirax (mrxs)
- Olympus (vsi)
- More slide scanners to be added!
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You have a specific research question that needs to be answered? We offer custom development of image analysis pipelines for specific tasks, be it detection of cellular phenotypes or quantification of tissue structures. After discussing your goals with one of our experts, you will get a ready-to-use App and be a step closer to an impactful publication.
