George Gorgy

Hospital for Special Surgery

Papers

2

Total Citations

17

H-Index

2

About

George Gorgy is a rising researcher at the intersection of medical imaging, artificial intelligence, and spinal surgery. His work focuses on advancing surgical planning and intraoperative guidance for complex spinal procedures, particularly pedicle screw placement. Gorgy’s most-cited study, published in 2024, demonstrates that deep-learning-reconstructed lumbar spine 3D MRI can rival CT for surgical planning, enabling accurate geometric measurements and pedicle screw placement without ionizing radiation—a breakthrough with 14 citations in under a year. He also pioneered a comparative analysis showing that biplanar radiographs can assess intraoperative screw placement accuracy with near-equivalent reliability to three-dimensional imaging, potentially reducing the need for costly intraoperative CT. By merging quantitative imaging analysis with clinical workflow optimization, Gorgy is helping to make spinal surgery safer, more efficient, and less reliant on radiation. His early citation impact signals growing recognition of his contributions to precision spine surgery and AI-driven radiology.

Research Focus

Key Achievements

2
H-Index
2
Papers
17
Total Citations
9
Avg Citations/Paper
🏆 Most Cited Paper
Deep-learning reconstructed lumbar spine 3D MRI for surgical planning: pedicle screw placement and geometric measurements compared to CT
14 citations · 2024
📈 Most Prolific Year: 2024 (2 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Hospital for Special Surgery

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago