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Sirius Red Polarized

Quantify collagen type I (red) and type III (green) fibers in Sirius Red–stained polarized images, measuring region area and the area of red, green, and overlapping (double-positive) fibers.

metastructures

vascularization

sirius red, collagen I, collagen III, polarized light, fibres

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The Sirius Red Polarized App allows for quantification of collagen type I and type III based on Sirius Red Staining imaged with polarized light. It outputs the region area (µm2), the area of collagen type I = red fibres (µm2), collagen type III = green fibres (µm2) and overlapping fibres (µm2).

Image courtesy of Dr. Mortiz Uhlig, University Hospital RWTH Aachen

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Detection of collagen type I

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Detection of collagen type III

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Overlapping of collagen type I and III

vascularization

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Application Note

01 Jun, 2023

Evaluating the Distance of Tumor Cells from Blood Vessels

metastructures

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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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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.

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About Us

TissueGnostics provides advanced solutions for whole-slide imaging and image analysis in biological and clinical research. Our products help researchers to scan and analyze complex tissue samples, enabling more detailed insights into tissue structure, cellular interactions, and spatial cell landscape.

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