Spatial Response Identification for Flexible and Accurate Ultrasound Transducer Calibration and its Application to Brain Imaging

Cueto, Carlos; Cudeiro-Blanco, Javier; Agudo, Òscar Calderón; Guasch, Lluís; Tang, Meng-Xing

doi:10.1109/tuffc.2020.3015583

Cited by 8 publications

(11 citation statements)

References 34 publications

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“…In backpropagation, which is only applicable in transmission, the response of the transducer is reconstructed by running a model of wave propagation backwards in time until signals recorded experimentally with a hydrophone are projected onto the surface of the transducer. As we showed in previous work [14], both of these methods fail to achieve the accuracy that is required by ultrasound tomography techniques such as FWI. This led us to propose spatial response identification (SRI), an impulse response estimation algorithm that achieves higher experimental calibration performance than existing techniques.…”

Section: Introductionmentioning

confidence: 82%

“…In the following paragraphs, we review the formulation of SRI as presented in [14] for completeness. SRI assumes that the arbitrary transducer surface has a spatially varying response that can be parametrised as an IR and its effect is that of a convolution operation.…”

Section: A Spatial Response Identificationmentioning

confidence: 99%

“…This optimisation problem can be solved efficiently by using an adjoint gradient formulation for any cost function, any relevant PDE, and any arbitrary propagation medium. For a derivation of an adjoint solution for the L2-norm of the misfit between predicted and observed data and the second-order acoustic wave equation see [14].…”

Section: A Spatial Response Identificationmentioning

confidence: 99%

“…The hemispherical surfaces were discretised using 200 spatially distributed points, with each spatial point representing an IR filter of 3500 time steps. The number of points was chosen to ensure a density of at least 4 points per squared wavelength at the centre frequency of the transducers, 450 kHz [14]. The points were distributed over the surface of the hemisphere using Fibonacci spirals in order to generate an even distribution [15].…”

Section: B Calibration Setupmentioning

confidence: 99%

“…This was performed by assuming that the transducers behave as baffled pistons and deconvolving the expected infinitebandwidth response of the transducer and its experimentally measured response. Deconvolution was chosen for the comparison because, on average, it performs better than other standard calibration techniques [14].…”

Section: B Calibration Setupmentioning

confidence: 99%

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Spatial response identification enables robust experimental ultrasound computed tomography

Cueto,

Guasch,

Cudeiro

et al. 2021

Preprint

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Ultrasoundcomputed tomography techniques have the potential to provide clinicians with 3D, quantitative and high-resolution information of both soft and hard tissues such as the breast or the adult human brain. Their practical application requires accurate modelling of the acquisition setup: the spatial location, orientation, and impulse response of each ultrasound transducer. However, existing calibration methods fail to accurately characterise these transducers unless their size can be considered negligible when compared to the dominant wavelength, which reduces signal-to-noise ratios below usable levels in the presence of high-contrast tissues such as the skull. In this paper, we introduce a methodology that can simultaneously estimate the location, orientation, and impulse response of the ultrasound transducers in a single calibration. We do this by extending spatial response identification, an algorithm that we have recently proposed to estimate transducer impulse responses. Our proposed methodology replaces the transducers in the acquisition device with a surrogate model whose effective response matches the experimental data by fitting a numerical model of wave propagation. This results in a flexible and robust calibration procedure that can accurately predict the behaviour of the ultrasound acquisition device without ever having to know where the real transducers are or their individual impulse response. Experimental results using a ring acquisition system show that spatial response identification produces calibrations of significantly higher quality than standard methodologies across all transducers, both in transmission and in reception. Experimental fullwaveform inversion reconstructions of a tissue-mimicking phantom demonstrate that spatial response identification generates more accurate reconstructions than those produced with standard calibration techniques.

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Section: Introductionmentioning

confidence: 82%

Section: A Spatial Response Identificationmentioning

confidence: 99%

Section: A Spatial Response Identificationmentioning

confidence: 99%

Section: B Calibration Setupmentioning

confidence: 99%

Section: B Calibration Setupmentioning

confidence: 99%

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