Author

Dmytro Fishman

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Preprint Sep 2026

Diffusion-Based Tumor Inpainting for Renal Segmentation under Clinical Data Scarcity

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. We propose a diffusion-based inpainting framework that synthesizes anatomically plausible renal tumors within healthy CT scans, requiring no...

Ekaterina Sedykh, Salme Ussanov, Dmytro Fedorenko et al. · 0 citations

Preprint Sep 2026

Weakly-supervised Kidney Tumor Classification from CT Scans with Multi-Instance Learning and Anatomical Filtering

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 scan-level labels alone reduces annotation requirements but introduces challenges: low supervision ratios and large input volumes make mode...

Joonas Ariva, Dmytro Fishman · 0 citations

#artificial intelligence Preprint Aug 2026

QCell: Recombining and Aligning Cell Queries for Overlapping Instance Segmentation

QCell is presented, a novel query-based model that de-overlaps cell instances in microscopy scenes and outperforms state-of-the-art methods across multiple benchmarks, achieving +2.2 AP and +2.7 AJI on ISBI2014.

Yaroslav Prytula, A. Popov, Dmytro Fishman · 0 citations