Experimental reconstruction of temperature distribution at a depth through thermal acoustic radiation

Passechnik, V.I.; Аносов, А. А.; Isrefilov, M. G.; Ерофеев, А. В.

doi:10.1016/s0041-624x(98)00036-5

Cited by 19 publications

(7 citation statements)

References 2 publications

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“…In passive methods, the thermometry probe is only in receive mode without transmitting any wave to the medium. The radiated acoustic wave is as a result of chaotic motions of atoms in heated area [33]. Acoustic thermometry methods have some advantages in comparison with microwave or magnetic resonance thermometries.…”

Section: Passive Thermometrymentioning

confidence: 99%

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A Review of Ultrasound Thermometry Techniques

Amiri¹,

Makkiabadi²

2020

fbt

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Acoustic thermometry is one of non-invasive methods to measure the temperature inside tissue area. Especially, when using the thermal therapy techniques such as High Intensity Focused Ultrasound (HIFU) and other thermal based methods, thermal assessment of heated area seems to be necessary. Some of acoustic properties of medium are temperature dependent; therefore, evaluation of temperature dependent parameters will be an indirect and non-invasive approach in thermometry. In this paper some of thermometry methods based on changes in acoustic properties of medium have been reviewed. The published methods are classified in two main categories: passive and active thermometry. In the passive thermometry, the thermal measurement probes, induced no acoustic signals to the medium, but they receive the radiated signals from the heated medium. In active method, the thermometry probe transmits a signal into the heated region and receives the echoes, then the received RF signals are processed in order to measure the temperature.

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Section: Passive Thermometrymentioning

confidence: 99%

“…Where in Equation 15, T, p are absolute temperature acoustic pressure, respectively. For an inhomogeneous medium, the derived temperature from acoustic pressure denotes the acoustic brightness temperature [33].…”

Section: ∝ 2 (15)mentioning

confidence: 99%

A Review of Ultrasound Thermometry Techniques

Amiri¹,

Makkiabadi²

2020

fbt

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“…The chamber had an acoustically transparent window made of lavsan film (Prana-Polimer, Perm, Russia) with a thickness of 0.03 mm. The thermal acoustic radiation emitted by the forearm of the human volunteer or by the plasticine slab (8) was measured in the apparatus, as shown in Fig. 1.…”

Section: B Experimental Setupmentioning

confidence: 99%

“…6 This method allows the calculation of internal temperatures at depths of up to 7 cm. 7,8 The thermal acoustic radiation is generated by the random motion of atoms and molecules. Note a difference between the active and passive acoustic thermometry.…”

mentioning

confidence: 99%

Passive estimation of internal temperatures making use of broadband ultrasound radiated by the body

Аносов

Kazansky

Subochev

et al. 2015

The Journal of the Acoustical Society of America

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The internal temperatures of plasticine models and the human forearm in vivo were determined, based on remote measurements of their intrinsic ultrasonic radiation. For passive detection of the thermal ultrasonic radiation an acoustic radiometer was developed, based on a broadband 0.8-3.3 MHz disk-shaped ultrasonic detector with an 8 mm aperture. To reconstruct temperature profiles using the experimentally measured spectra of thermal acoustic radiation a priori information was used regarding the temperature distribution within the objects being investigated. The temperature distribution for heated plasticine was considered to be a monotonic function. The distribution for the human forearm was considered to fit a heat equation incorporating blood flow parameters. Using sampling durations of 45 s the accuracy of temperature measurement inside a plasticine model was 0.5 K. The measured internal temperature of the forearm in vivo, at 36.3 °C, corresponded to existing physiological data. The results obtained verify the applicability of this passive method of wideband ultrasonic thermometry to medical applications that involve local internal heating of biological tissue.

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“…Some sort of spatial discretization or function approximation tools have to be used to transform it into a finite dimensional expression and hence can allow it to be saved, processed or handled by human. In the literature, the traditional tools used for reconstructing 3D temperature field involved the Least Square method, Fourier series and polynomial interpolation [1][2][3][4][5][6][7][8][9]. However, all of these reconstruction algorithms are unsatisfactory.…”

Section: Introductionmentioning

confidence: 99%

3D reconstruction of temperature field using Gaussian Radial Basis Functions (GRBF)

Liu

Cao

et al. 2015

2015 IEEE International Conference on Information and Automation

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3D temperature field reconstruction is of practical interest to the power, transportation and aviation industries and it also opens up opportunities for real time control or optimization of high temperature fluid or combustion process. In this paper, a new algorithm for the reconstruction of 3D temperature field is proposed based on Gaussian Radial Basis Functions (GRBF). A 3D temperature field is a space distribution profile evolving over time which is infinite dimensional in nature, the proposed GRBF-based approach can approximate the temperature field as a finite summation of space-dependent basis functions and time-dependent coefficients. According to the acoustic pyrometry principle, these Gaussian functions are integrated along a number of paths which are determined by the number and distribution of sensors. This inversion problem to estimate the unknown parameters of the Gaussian functions can be solved with the measured times-of-flight (TOF) of acoustic waves and the length of propagation paths using the recursive least square method (RLS). Compared with polynomial interpolation and functions parameterization, GRBF provides better approximation capability for most nonlinear functions over irregular regions. It is also superior in scalability and more efficient when extended to higher dimensional space. The simulation result shows an error less than 2% between the reconstructed temperature field and the ideal one. It demonstrates the availability and efficiency of GRBF framework for temperature field reconstruction.

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Experimental reconstruction of temperature distribution at a depth through thermal acoustic radiation

Cited by 19 publications

References 2 publications

A Review of Ultrasound Thermometry Techniques

A Review of Ultrasound Thermometry Techniques

Passive estimation of internal temperatures making use of broadband ultrasound radiated by the body

3D reconstruction of temperature field using Gaussian Radial Basis Functions (GRBF)

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