Identification of Denatured Biological Tissues Based on Improved Variational Mode Decomposition and Autoregressive Model during HIFU Treatment

Abstract

During high-intensity focused ultrasound (HIFU) treatment, the accurate identification of denatured biological tissue is an important practical problem. In this paper, a novel method based on the improved variational mode decomposition (IVMD) and autoregressive (AR) model was proposed, which identified denatured biological tissue according to the characteristics of ultrasonic scattered echo signals during HIFU treatment. Firstly, the IVMD method was proposed to solve the problem that the VMD reconstruction signal still has noise due to the limited number of intrinsic mode functions (IMF). The ultrasonic scattered echo signals were reconstructed by the IVMD to achieve denoising. Then, the AR model was introduced to improve the recognition rate of denatured biological tissues. The AR model order parameter was determined by the Akaike information criterion (AIC) and the characteristics of the AR coefficients were extracted. Finally, the optimal characteristics of the AR coefficients were selected according to the results of receiver operating characteristic (ROC). The experiments showed that the signal-to-noise ratio (SNR) and root mean square error (RMSE) of the reconstructed signal obtained by IVMD was better than those obtained by variational mode decomposition (VMD). The IVMD-AR method was applied to the actual ultrasonic scattered echo signals during HIFU treatment, and the support vector machine (SVM) was used to identify the denatured biological tissue. The results show that compared with sample entropy, information entropy, and energy methods, the proposed IVMD-AR method can more effectively identify denatured biological tissue. The recognition rate of denatured biological tissue was higher, up to 93.0%.