13 citations · 28 across the 4 of their papers we have counts for
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cs.CV2025
A deep learning framework for efficient pathology image analysis
Peter Neidlinger, Tim Lenz, Sebastian Foersch +24
Artificial intelligence (AI) has transformed digital pathology by enabling biomarker prediction from high-resolution whole-slide images (WSIs). However, current methods are computa…
cs.CV2024★ 2 cited
Unsupervised Foundation Model-Agnostic Slide-Level Representation Learning
Tim Lenz, Peter Neidlinger, Marta Ligero +3
Representation learning of pathology whole-slide images (WSIs) has primarily relied on weak supervision with Multiple Instance Learning (MIL). This approach leads to slide represen…