3 citations · 4 across the 7 of their papers we have counts for
4 papers · 1 filter
Diffusion-Based Tumor Inpainting for Renal Segmentation under Clinical Data Scarcity
Ekaterina Sedykh, Salme Ussanov, Dmytro Fedorenko +1
Deep learning segmentation of renal tumors requires large annotated datasets, yet clinical deployments typically offer only a handful of tumor-positive cases from the target site.…
Weakly-supervised Kidney Tumor Classification from CT Scans with Multi-Instance Learning and Anatomical Filtering
Joonas Ariva, Dmytro Fishman
Deep learning models for CT scan analysis are often limited by the scarcity of precise pixel-level annotations, which require significant radiologist effort to produce. Training on…
QCell: Recombining and Aligning Cell Queries for Overlapping Instance Segmentation
Yaroslav Prytula, Anton Popov, Dmytro Fishman
Instance segmentation of overlapping cells in microscopy remains challenging due to semi-transparent structures that produce weak boundaries and mixed visual evidence in overlap re…
CellNet -- Localizing Cells using Sparse and Noisy Point Annotations
Benjamin Eckhardt, Dmytro Fishman, Stuart Fawke +3
Counting living cells is an important step in many biological research workflows. Our collaborators at the Wellcome Sanger Institute study vital genes in humans via large scale sat…