Noninvasive tissue temperature estimation via state-covariance spectral estimation

We address noninvasive temperature estimation from pulse-echo radio frequency signals obtained by standard diagnostic ultrasound imaging equipment. In particular, we use a novel spectral estimation technique based on state-covariance subspace analysis for tracking frequency shifts at two or more harmonic frequencies associated with temperature change. The new approach is shown to produce superior frequency shift estimates when compared to conventional high-resolution spectral estimation methods. The experimental results validate the theoretical prediction of existing harmonically-related peaks in the echo signal spectrum.