The following publications are possibly variants of this publication:
- Precise laminae segmentation based on neural network for robot-assisted decompressive laminectomyQian Li, Zhijiang Du, Hongjian Yu. cmpb, 209:106333, 2021. [doi]
- State recognition of decompressive laminectomy with multiple information in robot-assisted surgeryYu Sun 0018, Li Wang, Zhongliang Jiang, Bing Li, Ying Hu, Wei Tian. artmed, 102:101763, 2020. [doi]
- Bone Layer Perception in Milling Process Based on Video Sequence Images during Robot-assisted LaminectomyHaiyang Li, Meng Li, Xiaozhi Qi, Yuanyuan Yang, Ying Hu 0001. robio 2022: 1458-1463 [doi]
- A Stability and Safety Control Method in Robot-Assisted Decompressive Laminectomy Considering Respiration and Deformation of SpineMeng Li, Xiaozhi Qi, Yu Sun 0018, Bing Li 0015, Ying Hu 0001, Wei Tian. tase, 20(1):258-270, 2023. [doi]
- Model-Observer Based Quality Measures for Decompressed Medical ImagesDunling Li, Murray H. Loew. isbi 2004: 832-835
- Cutting Depth Monitoring Based on Milling Force for Robot-Assisted LaminectomyZhongliang Jiang, Xiaozhi Qi, Yu Sun 0018, Ying Hu, Guillaume Zahnd, Jianwei Zhang 0001. tase, 17(1):2-14, 2020. [doi]