An automatic intelligent simulation system and method for human bearing joint structure based on medical images
Through modules such as AI image segmentation and semantic recognition, parametric structure processing, and adaptive material assignment, the entire process from medical imaging to mechanical evaluation is automated, solving the problems of time-consuming joint structure information extraction and cumbersome model building in existing technologies. This improves simulation efficiency and the objectivity of results, and supports comparative analysis of multiple processing schemes.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- JILIN UNIVERSITY
- Filing Date
- 2026-04-10
- Publication Date
- 2026-07-07
AI Technical Summary
In existing technologies, the extraction of joint structure information from medical images relies on manual identification and segmentation, which is time-consuming and easily affected by subjective factors. Furthermore, the process of establishing joint structure models is cumbersome, making it difficult to achieve integrated automatic processing from images to simulations. It also lacks objectivity and systematicity in parametric simulation and mechanical evaluation of processing schemes.
The AI image segmentation and semantic recognition module automatically generates tissue semantic tags, and the 3D model is constructed by combining the 3D reconstruction and topology repair module. Different processing schemes are generated through the parametric structure processing simulation module, the adaptive material property assignment module automatically assigns material parameters, and the automatic load and boundary condition generation module automatically generates the conditions required for simulation. Finally, the results are output through the finite element simulation and mechanical evaluation module.
It achieves full automation from medical imaging to mechanical assessment, improves simulation efficiency and repeatability, provides digital comparative analysis of multiple processing schemes, and enhances the objectivity of simulation results and their value in supporting clinical decision-making.
Smart Images

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