Nataliya Kovalchuk

Stanford University

Papers

1

Total Citations

32

H-Index

1

About

Dr. Nataliya Kovalchuk’s research lies at the intersection of medical physics, radiation oncology, and artificial intelligence, with a focus on improving motion management in cancer therapy. Her most cited work introduces an attention-aware fully convolutional neural network combined with convolutional long short-term memory networks for ultrasound-based motion tracking during radiation treatment. This innovation addresses a critical challenge: precisely tracking tumor motion in real time using a LINAC-compatible robotic-arm-mounted ultrasound system, which offers high soft tissue contrast, no ionizing radiation, and cost-effectiveness. With 32 citations, this paper demonstrates her impact in advancing non-invasive, AI-driven solutions for adaptive radiotherapy. Dr. Kovalchuk’s contributions are notable for integrating deep learning with clinical imaging to enhance treatment accuracy and patient safety. Her work has been recognized as a promising option for motion management, bridging the gap between cutting-edge computational methods and practical clinical applications. For students and researchers, her research exemplifies how AI can transform real-time image guidance in radiation oncology, offering a compelling model for interdisciplinary innovation in medical physics.

Research Focus

Key Achievements

1
H-Index
1
Papers
32
Total Citations
32
Avg Citations/Paper
🏆 Most Cited Paper
Attention‐aware fully convolutional neural network with convolutional long short‐term memory network for ultrasound‐based motion tracking
32 citations · 2019
📈 Most Prolific Year: 2019 (1 Papers)
🤝 Key Collaborators: 8
🏛 Institutions: Stanford University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago