Non-Invasive Differential Temperature Monitoring Using Sensor Array for Microwave Hyperthermia Applications: A Subspace-Based Approach

Abstract

Non-invasive temperature monitoring is highly valuable in applications such as microwave hyperthermia treatment, where overheating may damage healthy tissue. This paper presents a subspace-based method for real-time temperature monitoring using a sensor array configuration. The proposed method improves upon the conventional Born approximation (BA) approach by accurately estimating the total field through primary induced currents. The temperature-dependent dielectric properties of breast tissues are modeled using data from porcine tissues, and a sigmoid function is employed to create realistic temperature transition zones in the numerical breast phantom. The method is validated through extensive simulations under noise-free and noisy conditions (SNR = 30 dB and 20 dB). The results demonstrate that our method maintains consistent performance across different temperature levels (38–45 °C), achieving reconstruction accuracy within ±0.2 °C at SNR = 30 dB and ±0.5 °C at SNR = 20 dB. While the computational overhead of calculating primary induced currents slightly increases the overall processing time, it leads to a faster convergence in the cost function minimization. These findings suggest that the proposed method offers a promising solution for real-time temperature monitoring in microwave hyperthermia applications.