13 citations · 13 across the 1 of their papers we have counts for
3 papers
Lumen: Parameter-Efficient Alignment of Pretrained Vision and Language Encoders for Zero-Shot Computational Pathology
Kiarash Tajbakhsh, Abdelrahman Faqieh, Michael Jopiti +9
Pathology vision-language models are commonly built by pretraining or fine-tuning large encoders on paired image-caption data. We asked whether a pathology vision-language model ca…
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…
Benchmarking foundation models as feature extractors for weakly-supervised computational pathology
Peter Neidlinger, Omar S. M. El Nahhas, Hannah Sophie Muti +13
Advancements in artificial intelligence have driven the development of numerous pathology foundation models capable of extracting clinically relevant information. However, there is…