1 citations · 2 across the 3 of their papers we have counts for
3 papers
DistillPath: An Efficient 22M Distilled Pathology Encoder Approaching Large Foundation Model Performance
Ramon Kaspar, Andrey Ignatov, Valentina Boeva
Many high-performing pathology tile encoders are now foundation models with hundreds of millions to over a billion parameters. Encoding and storing the thousands of tiles in each w…
Histopathological Image Classification with Cell Morphology Aware Deep Neural Networks
Andrey Ignatov, Josephine Yates, Valentina Boeva
Histopathological images are widely used for the analysis of diseased (tumor) tissues and patient treatment selection. While the majority of microscopy image processing was previou…
scTree: Discovering Cellular Hierarchies in the Presence of Batch Effects in scRNA-seq Data
Moritz Vandenhirtz, Florian Barkmann, Laura Manduchi +2
We propose a novel method, scTree, for single-cell Tree Variational Autoencoders, extending a hierarchical clustering approach to single-cell RNA sequencing data. scTree corrects f…