2 papers
eess.IV2026
Destroy Me: Automatic Artifact Generation for Histopathology Images
Zuzanna Krawczyk-Borysiak, Adam Krawczyk, Mateusz Miller +4
Deep learning's diagnostic utility in pathology is constrained by model vulnerability to real-world data imperfections. While current strategies favor "perfect data" by filtering l…
cs.CV2026
COGENT: Counterfactual Gaussian Explanations for Volumetric Medical Images
Dorian Rząsa, Bartosz Zabdyr, Krzysztof Piekarz +7
Explainability is essential for deploying deep learning models in high-stakes medical applications. Existing explainability methods for volumetric imaging predominantly operate in…