Paul Neculoiu

Papers

1

Total Citations

78

H-Index

1

About

Dr. Paul Neculoiu is a pioneering researcher at the intersection of artificial intelligence and surgical oncology, whose work is redefining precision in robotic surgery. His primary research focuses on developing deep learning models to enhance intraoperative decision-making, particularly by automating the segmentation of critical anatomical structures. Dr. Neculoiu’s most cited contribution, a 2021 study on automated segmentation of loose connective tissue fibers (LCTFs) in robot-assisted gastrectomy (78 citations), demonstrates how AI can predict safe dissection planes, effectively augmenting a surgeon’s cognitive and visual capabilities. This work not only reduces operative risk but also lays the groundwork for real-time, AI-guided surgical navigation. By translating complex anatomical patterns into actionable, data-driven insights, Dr. Neculoiu is advancing the frontier of computer-assisted surgery, with his findings serving as a cornerstone for future innovations in minimally invasive oncology. His research holds profound implications for training, safety, and patient outcomes, marking him as a key figure in the evolving field of surgical AI.

Research Focus

Key Achievements

1
H-Index
1
Papers
78
Total Citations
78
Avg Citations/Paper
🏆 Most Cited Paper
Automated segmentation by deep learning of loose connective tissue fibers to define safe dissection planes in robot-assisted gastrectomy
78 citations · 2021
📈 Most Prolific Year: 2021 (1 Papers)
🤝 Key Collaborators: 12

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago