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eess.IV2026
Explainable histomorphology-based survival prediction of glioblastoma, IDH-wildtype
Jan-Philipp Redlich, Friedrich Feuerhake, Stefan Nikolin +12
Glioblastoma, IDH-wildtype (GBM-IDHwt) is the most common malignant brain tumor. While histomorphology is a crucial component of GBM-IDHwt diagnosis, it is not further considered f…
eess.IV2024
Continual Domain Incremental Learning for Privacy-aware Digital Pathology
Pratibha Kumari, Daniel Reisenbüchler, Lucas Luttner +3
In recent years, there has been remarkable progress in the field of digital pathology, driven by the ability to model complex tissue patterns using advanced deep-learning algorithm…
eess.IV2024
Unsupervised Latent Stain Adaptation for Computational Pathology
Daniel Reisenbüchler, Lucas Luttner, Nadine S. Schaadt +2
In computational pathology, deep learning (DL) models for tasks such as segmentation or tissue classification are known to suffer from domain shifts due to different staining techn…