Search Results for author:
Found 2 papers, 2 papers with code
Spatially Resolved Gene Expression Prediction from H&E Histology Images via Bi-modal Contrastive Learning
Our results demonstrate the potential of BLEEP to provide insights into the molecular mechanisms underlying tissue architecture, with important implications in diagnosis and research of various diseases.
MAESTER: Masked Autoencoder Guided Segmentation at Pixel Resolution for Accurate, Self-Supervised Subcellular Structure Recognition
Complete manual segmentation is unfeasible for large datasets, and while supervised methods have been proposed to automate segmentation, they often rely on manually generated ground truths which are especially challenging and time consuming to generate in biology due to the requirement of domain expertise.
Cannot find the paper you are looking for? You can
Submit a new open access paper.
