A model based approach to in vivo ultrasound temperature estimation

Mahdi Bayat; John R. Ballard; Alyona Haritonova; Elias Wilken-Resman; Emad S Ebbini

doi:10.1109/ULTSYM.2014.0535

A model based approach to in vivo ultrasound temperature estimation

Mahdi Bayat, John R. Ballard, Alyona Haritonova, Elias Wilken-Resman, Emad S Ebbini

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

A model based technique for echo shift-based ultrasound temperature estimation is presented. First, the dynamic model is derived from direct discretization of the Pennes' bio-heat equation. This model is then used in a Kalman filter setting for temperature tracking using the incremental temperature changes acquired at each discrete grid point as the measurements. In addition to tissue heterogeneity, natural motions and deformations during in vivo ultrasound thermography play a significant role in degrading the performance of the ultrasound thermography. Using the model based approach, we present the results of temperature estimation during sub-therapeutic high intensity focus ultrasound (HIFU) shots in the hind limb of Copenhagen rats in vivo. The results show continuous tracking of the temperature via pure prediction during significant error cycles or displacement tracking failure. These results represent an early validation of a fully adaptive spatial-temporal filtering of thermography data to compensate for tissue motions and deformations in vivo.

Original language	English (US)
Title of host publication	IEEE International Ultrasonics Symposium, IUS
Publisher	IEEE Computer Society
Pages	2149-2152
Number of pages	4
ISBN (Electronic)	9781479970490
DOIs	https://doi.org/10.1109/ULTSYM.2014.0535
State	Published - Oct 20 2014
Event	2014 IEEE International Ultrasonics Symposium, IUS 2014 - Chicago, United States Duration: Sep 3 2014 → Sep 6 2014

Publication series

Name	IEEE International Ultrasonics Symposium, IUS
ISSN (Print)	1948-5719
ISSN (Electronic)	1948-5727

Other

Other	2014 IEEE International Ultrasonics Symposium, IUS 2014
Country/Territory	United States
City	Chicago
Period	9/3/14 → 9/6/14

Bibliographical note

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© 2014 IEEE.

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10.1109/ULTSYM.2014.0535

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Bayat, M, Ballard, JR, Haritonova, A, Wilken-Resman, E & Ebbini, ES 2014, A model based approach to in vivo ultrasound temperature estimation. in IEEE International Ultrasonics Symposium, IUS., 6932142, IEEE International Ultrasonics Symposium, IUS, IEEE Computer Society, pp. 2149-2152, 2014 IEEE International Ultrasonics Symposium, IUS 2014, Chicago, United States, 9/3/14. https://doi.org/10.1109/ULTSYM.2014.0535

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title = "A model based approach to in vivo ultrasound temperature estimation",

abstract = "A model based technique for echo shift-based ultrasound temperature estimation is presented. First, the dynamic model is derived from direct discretization of the Pennes' bio-heat equation. This model is then used in a Kalman filter setting for temperature tracking using the incremental temperature changes acquired at each discrete grid point as the measurements. In addition to tissue heterogeneity, natural motions and deformations during in vivo ultrasound thermography play a significant role in degrading the performance of the ultrasound thermography. Using the model based approach, we present the results of temperature estimation during sub-therapeutic high intensity focus ultrasound (HIFU) shots in the hind limb of Copenhagen rats in vivo. The results show continuous tracking of the temperature via pure prediction during significant error cycles or displacement tracking failure. These results represent an early validation of a fully adaptive spatial-temporal filtering of thermography data to compensate for tissue motions and deformations in vivo.",

author = "Mahdi Bayat and Ballard, {John R.} and Alyona Haritonova and Elias Wilken-Resman and Ebbini, {Emad S}",

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doi = "10.1109/ULTSYM.2014.0535",

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AU - Bayat, Mahdi

AU - Ballard, John R.

AU - Haritonova, Alyona

AU - Wilken-Resman, Elias

AU - Ebbini, Emad S

PY - 2014/10/20

Y1 - 2014/10/20

N2 - A model based technique for echo shift-based ultrasound temperature estimation is presented. First, the dynamic model is derived from direct discretization of the Pennes' bio-heat equation. This model is then used in a Kalman filter setting for temperature tracking using the incremental temperature changes acquired at each discrete grid point as the measurements. In addition to tissue heterogeneity, natural motions and deformations during in vivo ultrasound thermography play a significant role in degrading the performance of the ultrasound thermography. Using the model based approach, we present the results of temperature estimation during sub-therapeutic high intensity focus ultrasound (HIFU) shots in the hind limb of Copenhagen rats in vivo. The results show continuous tracking of the temperature via pure prediction during significant error cycles or displacement tracking failure. These results represent an early validation of a fully adaptive spatial-temporal filtering of thermography data to compensate for tissue motions and deformations in vivo.

AB - A model based technique for echo shift-based ultrasound temperature estimation is presented. First, the dynamic model is derived from direct discretization of the Pennes' bio-heat equation. This model is then used in a Kalman filter setting for temperature tracking using the incremental temperature changes acquired at each discrete grid point as the measurements. In addition to tissue heterogeneity, natural motions and deformations during in vivo ultrasound thermography play a significant role in degrading the performance of the ultrasound thermography. Using the model based approach, we present the results of temperature estimation during sub-therapeutic high intensity focus ultrasound (HIFU) shots in the hind limb of Copenhagen rats in vivo. The results show continuous tracking of the temperature via pure prediction during significant error cycles or displacement tracking failure. These results represent an early validation of a fully adaptive spatial-temporal filtering of thermography data to compensate for tissue motions and deformations in vivo.

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A model based approach to in vivo ultrasound temperature estimation

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