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Random Forest-Based Prediction of Bone Volume Fraction and Fracture Position from S-Parameters

Jianhe Li, Jinsui Meng, Yida Zhao, Zihe Wang, Liaoran Sun, Tao Shan

arXiv:2607.23563Published July 26, 20260 citations
  • cs.LG
  • action

Abstract

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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