IHC Immune Status in Situ
Segment tissue into tumor, stroma, and lymphocyte clusters using an AI classifier, detect hematoxylin-stained nuclei and immune phenotypes (e.g., CD45, CD3, CD20), and quantify spatial immune distribution.
bladder cancer, CD45, immune cells, tumor immune microenvironment, tertiary lymphoid structures, spatial analysis
The IHC Immune Status in Situ App is segmenting the tissue sections in morphological entities such as tumor, stroma and lymphocyte clusters using the AI Classifier. It furhter identifies single cells based on nuclei staining (hematoxylin) and detects immune cells based on appropriated stains (CD45, CD3, CD20 etc.). It also measures the distance of detected objects to the metastructure boundary, distance ranges can be defined. The App outputs parameters including area of the detected morphological entities, number/percentage of lymphocytes detected with the tissue entities as well as in certain proximities of the entities.
Original Image
Nuclei detection
Tumor/Stroma/lymphoid cluster detection
Proximity map tumor
Proximity map lymphoid cluster
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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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Custom App development
Perfectly tailored image analysis solutions for your research.
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.
