IHC-MARK Quantitation Software
Example of automatic assessment of nuclear protein expression in breast cancer tissues.
A novel unsupervised clustering approach was used to overcome one of the major barriers in image analysis - the identification of tumour nuclei from stromal tissue. The output shows positive tumour nuclei in red and negative tumour nuclei in blue. Data generated from the analysis include % positive nuclei and nuclear intensity.
IHC-Mark Algorithms Quantify:
- Intensity of staining
- Stain spatial density measurements
- Cell counting of Tumour specific cells
- Cell counting of Immune T-cells
- Differentiation of sub-cellular localisation ratios
Q. Why is this useful?
A. Gives greater insight to aid interpretation.
- 1,000 breast cancer patients
- 3,000 prostate cancer patients
- Multiple other tumour types
- Multiple biomarkers