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

Bingqing Li; Zijian Zhao; Faliang Chang

doi:10.1117/12.2203439

3 December 2015 Temperature distribution imaging using ultrasonic CT by maximum-likelihood expectation-maximization algorithm

Bingqing Li, Zijian Zhao, Faliang Chang

Author Affiliations +

Proceedings Volume 9794, Sixth International Conference on Electronics and Information Engineering; 97943D (2015) https://doi.org/10.1117/12.2203439
Event: Sixth International Conference on Electronics and Information Engineering, 2015, Dalian, China

Abstract

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.

Citation Download Citation

Bingqing Li, Zijian Zhao, and Faliang Chang "Temperature distribution imaging using ultrasonic CT by maximum-likelihood expectation-maximization algorithm", Proc. SPIE 9794, Sixth International Conference on Electronics and Information Engineering, 97943D (3 December 2015); https://doi.org/10.1117/12.2203439

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