Real-time ultrasound image reconstruction as an inverse problem on a GPU

Bueno, Paulo Agenor Alves; Zibetti, Marcelo V. W.; Maia, Joaquim Miguel

doi:10.1007/s11554-018-0806-8

Cited by 4 publications

(2 citation statements)

References 29 publications

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“…Consequently, all linear beamforming techniques (SAFT, PWI, TFM) produce images of limited spatial resolution, in particular showing oscillations due to the shape of ultrasonic pulses. In order to improve the resolution and the contrast of ultrasonic images, previous works adopted an inverse problem approach [19], [21]- [23]. In [19], we proposed a linear forward model which relates the FMC data to the reflectivity map of the inspected region, accounting for the acoustic responses of the transducers.…”

Section: Introductionmentioning

confidence: 99%

Fast Non-Stationary Deconvolution of Ultrasonic Beamformed Images for Nondestructive Testing

Laroche¹,

Bourguignon²,

Idier³

et al. 2021

IEEE Trans. Comput. Imaging

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This paper addresses high-resolution ultrasonic image reconstruction from Full Matrix Capture (FMC) data in the context of nondestructive testing (NDT). In order to reduce the numerical complexity, the time-domain data and ultrasonic model are projected into the image domain through a linear beamforming procedure. The resulting model is interpreted as a shift-variant convolution process, affected by non-stationary and colored noise. An interpolation procedure is built in order to account for the spatial variations of the resulting point spread function. Under the same methodological framework, an approximate whitening filter is proposed and incorporated in the forward model. Both constructions then allow fast computations and limited memory storage. Deconvolution is performed by minimizing the least-squares data misfit error, with a penalization term favoring sparsity and spatial continuity of the output images. Results with synthetic data show that the proposed approach gives performances close to the inversion of raw FMC data, while being computationally much more efficient. The method is finally applied to laboratory data for the inspection of a stainless steel block containing closely spaced and small sidedrilled holes calibrated flaws. Successful detection and separation is achieved for flaws with diameters six times smaller than the wavelength, and distant from each other by four times less than the resolution limit given by the Rayleigh criterion.

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Section: Introductionmentioning

confidence: 99%

Fast Non-Stationary Deconvolution of Ultrasonic Beamformed Images for Nondestructive Testing

Laroche¹,

Bourguignon²,

Idier³

et al. 2021

IEEE Trans. Comput. Imaging

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show abstract

“…To reduce the computational effort that arises when aiming for high estimation quality, efficient implementations exploiting the structure of the involved linear mappings need to be employed [31]. Often these structure exploiting algorithms allow a high degree of parallelization so that further speedups are possible by the use of a Graphical Processing Unit (GPU) [9], [32].…”

Section: Introduction a State Of The Artmentioning

confidence: 99%

Frequency Subsampling of Ultrasound Nondestructive Measurements: Acquisition, Reconstruction, and Performance

Kirchhof

Semper

Wagner

et al. 2021

IEEE Trans. Ultrason., Ferroelect., Freq. Contr.

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Detection and Separation of Close Flaws in Coarse-Grained Materials Using Ultrasonic Image Deconvolution

Laroche

Carcreff²,

Bourguignon

et al. 2022

J Nondestruct Eval

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Ultrasonic inspection of coarse-grained steels is a common challenge in various industrial fields. This task is often difficult because of acoustic scattering that creates structural noise in the ultrasonic signals and images. This drives inspections using low-frequency probes at the cost of a lower resolution of standard delay and sum (DAS) imaging techniques, such as the well-known total focusing method (TFM). The purpose of this paper is to present and evaluate the performances of an image reconstruction technique that aims at improving the resolution when inspecting industrial coarse-grained materials. An image deconvolution problem (with spatially varying blur) is formulated, relying on a forward model that links the TFM image to the acoustic reflectivity map. A particular attention is paid to the estimation of the PSF used for the deconvolution approach in an experimental context. The experiments are based on an austenitic-ferritic sample insonified using array probes at 3 MHz and 5 MHz placed in contact. The goal is to resolve two close reflectors corresponding to side drilled holes (SDH) with diameter 0.4 mm spaced by 0.4 mm edge to edge and positioned at different depths (10, 20, 30, 40 mm). This configuration corresponds to a critical case where the distance between the two reflectors is significantly inferior to the Rayleigh distance, that is the resolution limit of a DAS imaging system. These are typical cases where the employed frequency is actually too low and where a higher frequency probe should be used, which is not possible in practice, because it would affect the detection capability due to higher noise level. As predicted by the Rayleigh criterion, TFM is not able to separate the reflectors. The proposed image reconstruction method successfully resolves the majority of the reflectors with a rather accurate distance estimation. In the context of coarse-grained structure inspection, this approach enables the use of low-frequency probes, in order to improve the signal-to-noise ratio, while keeping high resolution capability.

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Real-time ultrasound image reconstruction as an inverse problem on a GPU

Cited by 4 publications

References 29 publications

Fast Non-Stationary Deconvolution of Ultrasonic Beamformed Images for Nondestructive Testing

Fast Non-Stationary Deconvolution of Ultrasonic Beamformed Images for Nondestructive Testing

Frequency Subsampling of Ultrasound Nondestructive Measurements: Acquisition, Reconstruction, and Performance

Detection and Separation of Close Flaws in Coarse-Grained Materials Using Ultrasonic Image Deconvolution

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