Temperature detection based on nonparametric statistics of ultrasound echoes

• Autorzy: Byra M. , Gambin B.
• Języki publikacji: EN

Abstrakty

EN

Different ultrasound echoes properties have been used for the noninvasive temperature monitoring. Temperature variations that occur during heating/cooling process induce changes in a random process of ultrasound backscattering. It was already proved that the probability distribution of the backscattered RF (radio frequency) signals is sensitive to the temperature variations. Contrary to previously used methods which explored models of scattering and involved techniques of fitting histograms to a special probability distribution two more direct measures of changes in statistics are proposed in this paper as temperature markers. They measure the ''distance'' between the probability distributions. The markers are the Kolmogorov Smirnov distance and Kulback-Leiber divergence. The feasibility of using such nonparametric statistics for non- invasive ultrasound temperature estimation is demonstrated on the ultrasounds data collected during series of heating experiments in which the temperature was independently registered by the classical thermometer or thermocouples.

Słowa kluczowe

EN

noninvasive temperature monitoring; nonparametric statistics; ultrasound backscattering

• Wydawca: Polskie Towarzystwo Akustyczne. Oddział Gdański
• Czasopismo: Hydroacoustics
• Rocznik: 2015
• Tom: Vol. 18
• Strony: 17—23
• Opis fizyczny: Bibliogr. 8 poz., rys.

Twórcy

autor

Byra M.

• Institute of Fundamental Technological Research, Pawinskiego 5B, 02-106 Warsaw, Poland

autor

Gambin B.

• Institute of Fundamental Technological Research, Pawinskiego 5B, 02-106 Warsaw, Poland

Bibliografia

• [1] Xiaonan Geng et al., Comparison of ultrasound temperature imaging with infrared thermometry during radio frequency ablation, Jpn. J. Appl. Phys., 53, 047001, 2014.
• [2] Hao-Li Liu et al, A unified approach to combine temperature estimation and elastography for thermal lesion determination in focused ultrasound thermal therapy, Phys. Med. Biol.56, 169, 2011.
• [3] B. Gambin, O. Doubrovina, Statistical properties of wavelet transform coefficients of backscattering signal from soft tissues and their phantoms, Hydroacoustics, Vol. 16, 59-66, 2013.
• [4] E. Kruglenko, B. Gambin, RF signal amplitude statistics during temperature changes in tissue phantoms, Hydroacoustics, Vol. 17, 115-122, 2014.
• [5] Quantitative Ultrasound in Soft Tissues, Eds. J. Mamou, M. L. Oelze, Springer 2013.
• [6] H. Piotrzkowska, J. Litniewski, E. Szymanska, M. Lewandowski, A. Nowicki, Statistics of envelope of high frequency ultrasound signal backscattered in human dermis, Hydroascoustic, Vol. 13, 205—214, 2010.
• [7] F. Destrempes, G. Clouthier, A critical review and uniformized reprezentation of statistical districution modeling the ultrasound echo envelope, Ultrasound in Med.& Biol., Vol. 36, 7, 1037–1051, 2010.
• [8] B. Gambin, E. Kruglenko, Temperature measurement by statistical parameters of ultrasound signal backscattered from tissue samples, Acta Physica Polonica A, (in press).