Lisa Kausch
Papers
2
Total Citations
31
H-Index
2
About
Lisa Kausch is a rising leader in the field of computer-assisted orthopedic surgery, with a primary focus on advancing spinal instrumentation through artificial intelligence and three-dimensional imaging. Her work centers on developing automated, high-precision tools for navigated lumbosacral pedicle screw placement, directly addressing the critical challenge of improving surgical accuracy and patient safety. Her most cited paper, "Development and validation of an automated planning tool for navigated lumbosacral pedicle screws using a convolutional neural network" (2022, 17 citations), introduces a novel deep-learning approach to streamline preoperative planning, a significant step toward reducing manual error and operative time. In a complementary study, "CT-Navigated Spinal Instrumentations–Three-Dimensional Evaluation of Screw Placement Accuracy in Relation to a Screw Trajectory Plan" (2022, 14 citations), Kausch provides a rigorous, quantitative framework for evaluating screw positioning against preoperative plans, moving beyond qualitative assessments common in the literature. This work establishes a new standard for measuring surgical precision. While early in her career, Kausch’s contributions are already shaping the future of minimally invasive spine surgery, demonstrating how machine learning can be harnessed to enhance both the planning and execution of complex navigated procedures.
Research Focus
Key Achievements
Top Papers
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