Abstract
To address the challenges in anterior cruciate ligament (ACL) reconstruction surgery-such as the high precision required for femoral tunnel positioning, lack of standardized procedures, and the time-consuming nature of preoperative planning-an intelligent femoral tunnel planning method based on CT imaging is proposed. This approach integrates techniques from 3D segmentation and reconstruction of knee joint CT images based on 3D U-Net and prior knowledge, with tunnel planning guided by the quadrant method and ratio analysis, aiming to improve the accuracy and standardization of both intra-articular and extra-articular femoral tunnel orifice localization. The proposed method was assessed through human-machine comparison and physical model validation. Experimental results demonstrate that the automated approach attains positioning accuracy comparable to that of expert manual operation, while offering faster speed and greater consistency.
| Original language | English |
|---|---|
| Pages (from-to) | 204-210 |
| Number of pages | 7 |
| Journal | Procedia Computer Science |
| Volume | 271 |
| DOIs | |
| Publication status | Published - 2025 |
| Event | 2025 International Conference on Biomimetic Intelligence and Robotics, ICBIR 2025 - Zhangye, China Duration: 26 Aug 2025 → 28 Aug 2025 |
Keywords
- Femoral Tunnel Planning
- Medical Image Segmentation
- Quadrant Method
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