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

Bingqing Li; Zijian Zhao; Faliang Chang

doi:10.1117/12.2203439

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

Bingqing Li, Zijian Zhao, Faliang Chang

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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.

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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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