2 citations · 2 across the 4 of their papers we have counts for
4 papers
Spatial Transcriptomics Expression Prediction from Histopathology Based on Cross-Modal Mask Reconstruction and Contrastive Learning
Junzhuo Liu, Markus Eckstein, Zhixiang Wang +2
Spatial transcriptomics is a technology that captures gene expression levels at different spatial locations, widely used in tumor microenvironment analysis and molecular profiling…
HIEGNet: A Heterogenous Graph Neural Network Including the Immune Environment in Glomeruli Classification
Niklas Kormann, Masoud Ramuz, Zeeshan Nisar +6
Graph Neural Networks (GNNs) have recently been found to excel in histopathology. However, an important histopathological task, where GNNs have not been extensively explored, is th…
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…
Overcoming Data Scarcity in Biomedical Imaging with a Foundational Multi-Task Model
Raphael Schäfer, Till Nicke, Henning Höfener +6
Foundational models, pretrained on a large scale, have demonstrated substantial success across non-medical domains. However, training these models typically requires large, compreh…