D7 - Breast cancer patient stratification using domain adaptation based lymphocyte detection in HER2 stained tissue sections
Ansh Kapil, Armin Meier, Anatoliy Shumilov, Susanne Haneder, Helen Angell, Günter Schmidt
We extend the CycleGAN architecture with a style-based generator and show the efficacy of the proposed domain adaptation-based method between two histopathology image domains - Hematoxylin and Eosin (H&E) and HER2 immunohistochemically (IHC) images. Using the proposed method, we re-used large set of pre-existing annotations for detection of tumor infiltrating lymphocytes (TILs), which were originally done on H&E, towards a TIL detector applicable on HER2 IHC images. We provide analytical validation of the resulting TIL detector. Furthermore, we show that the detected stromal TIL densities are significantly prognostic as a biomarker for patient stratification on a triple-negative breast cancer (TNBC) cohort.
Wednesday 7th July
D4-12 (short): Detection and Diagnosis 1 - 16:45 - 17:30 (UTC+2)