An Automatic Cutting Plane Planning Method Based on Multi-Objective Optimization for Robot-Assisted Laminectomy Surgery

Laminectomy represents an effective surgical procedure for the treatment of lumbar spinal stenosis. Due to the intricate anatomical structure of the lumbar spine, meticulous surgical path planning is essential to ensure the safety of the procedure and enhance the likelihood of successful outcomes. This study aims to implement multi-objective optimization techniques in the context of laminectomy, with a particular emphasis on identifying the optimal reference cutting path for the lamina. In clinical practice, the cutting path is typically characterized as a relatively straight line, akin to making an incision through the lamina with a sharp, rigid plane. Consequently, the optimal reference cutting path can be established by determining the ideal reference cutting plane. In our methodology, the cutting contour, defined as the intersection of the cutting plane with the lamina, is treated as a variable. Key features of the lamina are extracted and classified into three objective functions: the average thickness of the lamina, the derivative of the entry point of the cutting path, and the degree of overlap between adjacent vertebrae. We then apply multi-objective optimization algorithms and utilize the weighted sum method to solve the multi-objective problems in the laminectomy task. The experimental findings are validated by an enhanced laminectomy plane evaluation system, demonstrating that the automatically generated cutting planes achieve a high level of excellence (94%), thereby satisfying the surgical requirements validated by professional surgeons.