Artificial intelligence in digital pathology

Problems:

  • High time-consuming analysis of quantitative parameters evaluated in immunohistochemical staining
  • Bad accuracy of quantitative parameters evaluated in immunohistochemical staining
  • Counting of mitotic figures in tumor
  • Micrometastases presence evaluation in lymph nodes
  • Cytological sample screening

Our Solution:

Fully functional SW that helps pathologists determine the stage of cancer. ANNA offers a module for quantitative and semi-quantitative assessment of immunohistochemical staining of nuclear markers. It can determine the percentage of positive tumor cells out of the total number of tumor cells from the staining without counting the other cellular elements present in the total number of cells. It was developed in cooperation with the Oncological Institute of St. Elizabeth.

Benefits and results:

  • 60 %-time savings.
  • 30 % more served patients
  • Determine the exact percentage of positive tumor cells from overall tumor cells in immunohistochemical staining.
  • High increase accuracy of quantitative parameters evaluated in immunohistochemical staining.

Other solutions:

  • ANNA Micro-metastasis
  • ANNA Mitotic
  • ANNA Cytological