LAUSR

ABSTRACT Non-invasive monitoring of tissues’ temperatures is necessary for some diagnostic and therapeutic applications. Photoacoustic is a new hybrid biomedical imaging technique, combining the high-contrast of optical properties with the high spatial resolution of ultrasound. The estimation of model parameters that are temperature dependent was used in this work to indirectly measure the temperatures of tissues, as the solution of an inverse problem within the Bayesian framework of statistics. A two-dimensional case was examined, which is related to the hyperthermia treatment of cancer with laser heating in the near infrared range. Simulated measurements were used in the inverse analysis. The Markov Chain Monte Carlo method provided accurate estimation of the spatial distribution of the Gruneisen parameter and the temperature distribution in the region of interest could be recovered with discrepancies smaller than 0.03°C.