基于HIFU回波信号和多尺度模糊熵的生物组织变性识别研究OACSTPCD

To address the monitoring problem in high-intensity focused ultrasound(HIFU)therapy,a new method is proposed for identification of tissue damage without the need for additional monitoring sources.The method involves studying the multi-scale fuzzy entropy(MFE)of the fundamental and second harmonic of the HIFU echo.The HIFU echo signal is denoised using spectral subtraction,and then the fundamental and second harmonic components of the signal are extracted using the kullback-leibler divergence-optimized variational mode decomposition(KLD-VMD)method.Finally,the MFE combining the funda-mental and second harmonic is used to identify tissue damage.The validity of the method is verified using the equal error rate(EER),where a lower EER indicates better recognition.The study also compares the KLD-VMD method with other decomposi-tion methods such as VMD,EMD,and ITD,in combination with MFE for tissue damage identification.The experimental results demonstrate that the tissue damage identification based on KLD-VMD and MFE achieves an EER of 5.1%,which is better com-pared to the other methods.Furthermore,the results also show that combining the fundamental and second harmonics improves the identification performance compared to using either echo alone.This study provides a new monitoring method for HIFU therapy with potential practical applications.