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

2026/07/26 by Jianhe Li, Jinsui Meng, Yida Zhao +3
#cs.LG

paper · pdf

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.

Related

• Assessment of mechanical properties of bone trabeculae as an inverse problem of heterogeneous material modeling
• Delineating Bone Surfaces in B-Mode Images Constrained by Physics of Ultrasound Propagation
• Site-specific Quantification of Bone Quality using Highly Nonlinear Solitary Waves
• Bone Surface Reconstruction and Clinical Features Estimation from Sparse Landmarks and Statistical Shape Models: A feasibility study on the femur
• Development of the algorithm for differentiating bone metastases and trauma of the ribs in bone scintigraphy and demonstration of visual evidence of the algorithm -- Using only anterior bone scan view of thorax