Adaptive optimization on ultrasonic transmission tomography-based temperature image for biomedical treatment

Hyperthermia has proven to be beneficial to treating superficial malignancies, particularly chest wall recurrences of breast cancer. During hyperthermia, monitoring the time–temperature profiles in the target and surrounding areas is of great significance for the effect of therapy. An ultrasound-based temperature imaging method has advantages over other approaches. When the temperature around the tumor is calculated by using the propagation speed of ultrasound, there always exist overshoot artifacts along the boundary between different tissues. In this paper, we present a new method combined with empirical mode decomposition (EDM), similarity constraint, and continuity constraint to optimize the temperature images. Simulation and phantom experiment results compared with those from our previously proposed method prove that the EMD-based method can build a better temperature field image, which can adaptively yield better temperature images with less computation for assistant medical treatment control.