Temperature distribution imaging using ultrasonic CT by maximum-likelihood expectation-maximization algorithm

Ultrasonic CT is a new technique to measure temperature distribution in air. Based on the principle of ultrasonic CT technique, and the Maximum-Likelihood Expectation-Maximization (ML-EM) iteration algorithm, a novel method of temperature distribution imaging is proposed. In this method, Gaussian distribution model is applied instead of the traditional Poisson distribution model to the ML-EM iteration algorithm. And with Gaussian distribution, a new kind of ML-EM iteration algorithm is proposed. Using this method, the ultrasonic speed matrix can be calculated from projection data on a number of fixed propagation paths. And the 3D temperature distribution is obtained from the speed information. The simulation results prove the correctness and the validity of the proposed method.