用微波多通道参数预测骨骼体积分数与骨折位置
Random Forest-Based Prediction of Bone Volume Fraction and Fracture Position from S-Parameters
- 基于九天线微波扫描系统采集S参数，构建随机森林模型
- 实验与仿真均验证方法有效，可准确预测骨体积分数和骨折位置
- 适用于骨质疏松检测与骨折风险评估，适合医学成像研究者
本文提出一种基于多通道S参数的随机森林模型，用于预测骨体积分数（BVF）和骨折位置。设计并制作了九天线微波扫描系统以获取多通道S参数数据。开发了骨仿体模型，并通过实验验证所提方法的有效性。合成数据与实验结果均表明该方法具有良好的预测性能。
原文摘要 · Abstract (English)
In this paper, we propose a method for predicting bone volume fraction (BVF) and fracture position by constructing a random forest model based on multichannel S-parameters. A nine-antenna microwave scanning system is designed and fabricated to acquire the multichannel S-parameter data. Bone-mimicking phantoms are developed, and corresponding experiments are conducted to validate the effectiveness of the proposed approach. Both synthetic and experimental results demonstrate the validity of the method.
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