Publications
151
Citations
2,666
Est. group size
—
Recurring co-author estimate
Active years
27
Publishing since 1999
Yury Velichko works at the intersection of medical imaging and artificial intelligence, developing computer methods to analyze CT and MRI scans of organs such as the liver, pancreas, and brain. Much of the work focuses on automatically outlining organs and tumors (image segmentation) and using image features (radiomics) to predict how cancers respond to treatment. The research also explores collaborative training methods like federated learning, which lets hospitals build shared AI models without pooling patient data.
Publication activity has grown sharply, rising from a handful of papers per year in the late 2010s to a peak of roughly 48 in 2024, averaging about 18 per year over the last five years.
Generated by claude-opus-4-8 from public bibliographic data · Jul 11, 2026
- MDNet: Multi-Decoder Network for Abdominal CT Organs Segmentation
2025
- Large Scale MRI Collection and Segmentation of Cirrhotic Liver
Scientific Data · 2025
- A New Logic for Pediatric Brain Tumor Segmentation
2025
- Adaptive Aggregation Weights for Federated Segmentation of Pancreas MRI
2025
- Radiomics Models to Predict Tumor Response and Pneumonitis in Non-Small Cell Lung Cancer Patients Treated with Immunotherapy
Journal of Clinical Medicine · 2025
- Uncertainty-Guided Cross Attention Ensemble Mean Teacher for Semi-Supervised Medical Image Segmentation
2025
- Delta Radiomics and Tumor Size: A New Predictive Radiomics Model for Chemotherapy Response in Liver Metastases from Breast and Colorectal Cancer
Tomography · 2025
- Intracranial Metastases from Uterine Leiomyosarcoma: A Systematic Review and Case Illustration
Journal of Clinical Medicine · 2025
- IPMN Risk Assessment Under Federated Learning Paradigm
2025
- Multi-center evaluation of radiomics and deep learning to stratify malignancy risk of IPMNs
Research Square · 2025
- Cyst-X: AI-Powered Pancreatic Cancer Risk Prediction from Multicenter MRI in Centralized and Federated Learning
Research Square · 2025
- Large-scale multi-center CT and MRI segmentation of pancreas with deep learning
Medical Image Analysis · 2024
- Advances for Managing Pancreatic Cystic Lesions: Integrating Imaging and AI Innovations
Cancers · 2024
- Large-Scale Multi-Center CT and MRI Segmentation of Pancreas with Deep Learning
arXiv (Cornell University) · 2024
- Beyond Self-Attention: Deformable Large Kernel Attention for Medical Image Segmentation
2024
- arXiv (Cornell University)×22
- PubMed×9
- Cancer Research×7
- Journal of Clinical Oncology×6
- Lecture notes in computer science×4
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 11, 2026.
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