Lianne R. Johnson
Papers
2
Total Citations
9
H-Index
2
About
Dr. Lianne R. Johnson is a pioneering researcher at the intersection of robotic surgery, computer vision, and quantitative performance assessment. Her work focuses on developing objective, data-driven methods to evaluate and enhance surgical precision in robot-assisted procedures. Dr. Johnson’s major contributions include the first quantitative comparison of manual versus robotic-assisted carotid artery stenting, using tool-tip kinematic data and motion-based metrics to demonstrate the advantages of robotic systems. This foundational study, with 7 citations, provides a critical framework for future surgical robotics research. She has also advanced the field of surgical video analysis by developing multi-frame context-driven deep learning models for automated tracking of surgical tool keypoints. This work, published in 2025, enables downstream applications such as skill assessment, expertise evaluation, and safety zone delineation. Dr. Johnson’s research is instrumental in moving surgical evaluation from subjective observation to objective, data-driven measurement, paving the way for safer, more effective robotic surgeries and improved training methodologies for the next generation of surgeons.
Research Focus
Key Achievements
Top Papers
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