Andreas Unterberg
Papers
2
Total Citations
31
H-Index
2
About
Andreas Unterberg is a leading figure in the field of computer-assisted spinal surgery, with a particular focus on the integration of artificial intelligence and advanced imaging to enhance surgical precision. His major contributions center on the development and validation of automated planning tools for navigated spinal instrumentation. Notably, he pioneered the use of convolutional neural networks to automate the planning of lumbosacral pedicle screw trajectories, a breakthrough that promises to reduce operative time and human error. His work also includes rigorous three-dimensional evaluations of screw placement accuracy, moving beyond traditional qualitative assessments to provide quantitative metrics of surgical performance relative to preoperative plans. With his most-cited papers from 2022 already accumulating over 30 citations, Unterberg’s research is rapidly shaping best practices in navigated spine surgery. His achievements demonstrate a commitment to translating cutting-edge computational methods into tangible clinical improvements, making him a key voice in the evolution of precision spine surgery.
Research Focus
Key Achievements
Top Papers
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- 2