Temperature Monitoring During Microwave Hyperthermia Based on BP-Nakagami Distribution

Objective-The purpose of this study is to accurately monitor temperature during microwave hyperthermia. We propose a temperature estimation model BPNakagami based on neural network for Nakagami distribution. Methods-In this work, we designed the microwave hyperthermia experiment of fresh ex vivo pork tissue and phantom, collected ultrasonic backscatter data at different temperatures, modeled these data using Nakagami distribution, and calculated Nakagami distribution parameter m. A neural network model was built to train the relationship between Nakagami distribution parameter m and temperature, and a BP-Nakagami temperature model with good fitting was obtained. The temperature model is used to draw the two-dimensional temperature distribution map of biological tissues in microwave hyperthermia. Finally, the temperature estimated by the model is compared with the temperature measured by thermocouples. Results-The error between the temperature estimated by the temperature model and the temperature measured by the thermocouple is within 1 degrees C in the range of 25 degrees C-50 degrees C for ex vivo pork tissue, and the error between the temperature estimated by the temperature model and the temperature measured by the thermocouple is within 0.5 degrees C in the range of 25 degrees C-50 degrees C for phantom. Conclusions-The results show that the temperature estimation model proposed by us is an effective model for monitoring the internal temperature change of biological tissues.