A new beamforming process based on the phase dispersion analysis

Developing new imaging methods needs to establish some proofs of concept before implementing them on real-time scenarios. Nowadays, the high computational power reached by multi-core CPUs and GPUs have driven the development of software-based beamformers. Taking this into account, a library for the fast generation of ultrasound images is presented. It is based on Synthetic Aperture Imaging Techniques (SAFT) and it is fast because of the use of parallel computing techniques. Any kind of transducers as well as SAFT techniques can be defined although it includes some pre-built SAFT methods like 2R-SAFT and TFM. Furthermore, 2D and 3D imaging (slicebased or full volume computation) is supported along with the ability to generate both rectangular and angular images. For interpolation, linear and polynomial schemes can be chosen. The versatility of the library is ensured by interfacing it to Matlab, Python and any programming language over different operating systems. On a standard PC equipped with a single NVIDIA Quadro 4000 (256 cores), the library is able to calculate 262,144 pixels in ≈105 ms using a linear transducer with 64 elements, and 2,097,152 voxels in ≈ 5 seconds using a matrix transducer with 121 elements when TFM is applied.

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“… Coherence factor. Commands for the application of coherence factors are given [10].  Matlab©/Python bindings.…”

Section: Cheetah Core Featuresmentioning

confidence: 99%

Cheetah: A Library for Parallel Ultrasound Beamforming in Multi-Core Systems

Romero-Laorden¹,

Martín-Arguedas²,

Villazón-Terrazas³

et al. 2015

JAMP

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“…The latest algorithms attempt aim to both to increase the measurement speed and to reduce the influence of the transmitted signal in the case of defects located very close to the phased array [39]. There is also great potential in taking into account the phase of the received Lamb waves [19,40].…”

Section: Introductionmentioning

confidence: 99%

On Dispersion Compensation for GAW-Based Structural Health Monitoring

Backer

Fairuschin

Drese

2023

Sensors

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Guided acoustic waves (GAW) have proven to be a useful tool for structural health monitoring (SHM). However, the dispersive nature of commonly used Lamb waves compromises the spatial resolution making it difficult to detect small or weakly reflective defects. Here we demonstrate an approach that can compensate for the dispersive effects, allowing advanced algorithms to be used with significantly higher signal-to-noise ratio and spatial resolution. In this paper, the sign coherence factor (SCF) extension of the total focusing method (TFM) algorithm is used. The effectiveness is examined by numerical simulation and experimentally demonstrated by detecting weakly reflective layers with a highly dispersive A0 mode on an aluminum plate, which are not detectable without compensating for the dispersion effects.

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“…Camacho et al [5] present the analysis of the phase variance and Martínez-Graullera et al [6] the spectral analysis of the phase distribution. Both present coherence factors that are multiplied by the TFM images to improve contrast and dynamic range.…”

Section: Introductionmentioning

confidence: 99%

“…Both present coherence factors that are multiplied by the TFM images to improve contrast and dynamic range. Based on [5], [6], the instantaneous phase is used in this work to improve reflectors detectability, reducing side and grating lobes effects in images obtained by sparse linear arrays configurations. Results are shown for a simulated point spread function (2λ-pitch, 32 elements array), a medical phantom (7λ-pitch, 32 elements) and an aluminum plate (λ-pitch, 8 elements).…”

Section: Introductionmentioning

confidence: 99%

The use of instantaneous phase for improving sparse arrays images

Prado¹,

Higuti²,

Kitano³

et al. 2013

2013 IEEE International Ultrasonics Symposium (IUS)

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Sparse arrays have pitch larger than halfwavelength (λ/2) and there is a reduced number of elements in comparison with a full-populated array. Consequently, there is a reduction in cost, data acquisition and processing. However, conventional beamforming techniques result in large side and grating lobes, and consequently in image artifacts. In this work the instantaneous phase of the signals is used in a beamforming technique instead of the instantaneous amplitudes to improve images obtained from sparse arrays configurations. A threshold based on a statistical analysis and the number of signals used for imaging is applied to each pixel, in order to determine if that pixel is related to a defect or not. Three sets of data are used to evaluate the technique, considering medical and non-destructive testing: a simulated point spread function, a medical phantom and an aluminum plate with 2λ-, 7λ-and λ-pitch, respectively. The conventional amplitude image is superposed by the image improved by the instantaneous phase, increasing the reflectors detectability and reducing artifacts for all cases, as well as dead zone for the tested plate.

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A new beamforming process based on the phase dispersion analysis

Cited by 8 publications

References 3 publications

Cheetah: A Library for Parallel Ultrasound Beamforming in Multi-Core Systems

Cheetah: A Library for Parallel Ultrasound Beamforming in Multi-Core Systems

On Dispersion Compensation for GAW-Based Structural Health Monitoring

The use of instantaneous phase for improving sparse arrays images

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