2 citations · 3 across the 3 of their papers we have counts for
3 papers
cs.CV2026
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…
eess.IV2024★ 2 cited
NCT-CRC-HE: Not All Histopathological Datasets Are Equally Useful
Andrey Ignatov, Grigory Malivenko
Numerous deep learning-based solutions have been proposed for histopathological image analysis over the past years. While they usually demonstrate exceptionally high accuracy, one…
eess.IV2024★ 1 cited
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…