Cutting‑edge technology for quantifying the tumor microenvironment
Training data generated
by immunofluorescence staining
Predict from morphological features better than anywhere else with massively trained wet-based learning models.
Quantification of immune cells
Counting the numbers of lymphocytes, plasma cells and fibroblasts in the stroma
Understanding the compositional content within the ROI (Region of Interest)
Users can freely select regions and keep track of cell counts and percentages.
Patient stratification based on quantification data
Our AI can quantify tumor-infiltrating lymphocyte scores in any user-selected region.
Publications
-
AI-based quantification of TILs using hematoxylin and eosin and immunohistochemistry-stained slides in triple-negative breast cancer. American Society of Clinical Oncology (2024)
-
Deep learning-based quantitative assessment of tumor-infiltrating lymphocytes from hematoxylin and eosin-stained slides in triple-negative breast cancer: A prognostic study. American Society of Clinical Oncology (2024)
-
AI-powered quantification of tumor-infiltrating lymphocytes from H&E stained images in ovarian cancer and its association with PARP inhibitor therapy outcomes. (2025)
