A comparison between temporal and subband minimum variance adaptive beamforming

Diamantis, Konstantinos; Voxen, Iben Holfort; Greenaway, A. H.; Anderson, Thomas; Jensen, Jørgen Arendt; Sboros, Vassilis

doi:10.1117/12.2043602

Cited by 11 publications

(10 citation statements)

References 18 publications

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“…It is common to state that Capon beamforming applied to ultrasound imaging increases both contrast and resolution [1] [2]. In this paper we aim to show that the increased contrast is mainly a result of the increased resolution gained from the Capon beamformer.…”

Section: Introductionmentioning

confidence: 99%

Understanding contrast improvements from capon beamforming

Rindal

Åsen²,

Holm³

et al. 2014

2014 IEEE International Ultrasonics Symposium

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This paper investigates the contrast improvements seen when using adaptive (Capon) beamforming to create ultrasound images. Ultrasound images of cysts have been simulated using linear array imaging in Field II. The contrast of the cyst compared to the speckle surrounding it has been investigated, especially the improved edges produced by the Capon beamformer. We show that it is the improved edges that cause the contrast improvements. The resulting beampattern from the Capon beamformer has been compared to the beampattern from the conventional delay and sum (DAS) beamformer with different apodizations to show how the improved edges are generated. Finally, a bright inclusion was added to the simulation to demonstrate how the visual contrast changes when the image contains multiple intensity plateaus.

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Section: Introductionmentioning

confidence: 99%

Understanding contrast improvements from capon beamforming

Rindal

Åsen²,

Holm³

et al. 2014

2014 IEEE International Ultrasonics Symposium

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“…For example, the re-emission of the received transducer element responses can compensate for the wavefront distortion, caused by the changing impedance mismatch between the transducer face and the target material [26]- [28]. Alternatively, various adaptive beamforming approaches have shown that up to λ/12 lateral resolution in the localization of isolated point scatterers can be achieved [29], [30], and there is an early demonstration using raw ultrasound data from in-vivo measurements [31]. The results show that particularly Minimum Variance (MV) beamforming could be suited to the detection of vessel stenosis [32], and to real-time cardiac ultrasound imaging [33], providing improved lateral resolution.…”

Section: Introductionmentioning

confidence: 99%

Super-Resolution Axial Localization of Ultrasound Scatter Using Multi-Focal Imaging

Diamantis

Greenaway

Anderson

et al. 2018

IEEE Trans. Biomed. Eng.

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“…2) MV Beamforming for Point Scatterer Imaging: Substantial previous work has established an optimization methodology for use of the MV beamformer in the imaging of point scatterers [9], [10], [12]. This work alongside with other MV studies [6]- [8], [16], [27] has helped develop the MV beamformer, by investigating the impact of all MV-related parameters in the imaging of point scatterers.…”

Section: Methodsmentioning

confidence: 99%

“…where J is the exchange matrix and Tr is the matrix trace. The MV method was then used to beamform a single emission image [9], [10], by calculating an apodization weight for each pixel [16]. The pixel dimensions were 12.5 µm by 25 µm, with smaller lateral size that improves MV resolution [12].…”

Section: Methodsmentioning

confidence: 99%

“…Key to this hypothesis testing is a quantitative assessment of the lateral resolution based on the classical definition; that is the smallest possible distance between two point sources, located side-by-side that enables the display of two points as separate targets [26]. Single emission beamformed responses are used as they can significantly increase the acquisition rate without sacrificing resolution [9], [10], and are relevant to imaging fast-moving targets like MBs that are used in SRI [22]- [24].…”

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confidence: 99%

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Resolving Ultrasound Contrast Microbubbles Using Minimum Variance Beamforming

Diamantis

Anderson

Butler

et al. 2019

IEEE Trans. Med. Imaging

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Minimum Variance (MV) beamforming is known to improve the lateral resolution of ultrasound images and enhance the separation of isolated point scatterers. This paper aims to evaluate the adaptive beamformer's performance with flowing microbubbles (MBs), which are relevant to super-resolution ultrasound imaging. Simulations using point scatterer data from single emissions were complemented by an experimental investigation performed using a capillary tube phantom and the Synthetic Aperture Real-time Ultrasound System (SARUS). The MV performance was assessed by the minimum distance that allows the display of two scatterers positioned side-by-side, the lateral Full- Width-Half-Maximum (FWHM), and the Peak-Side-lobe-Level (PSL). In the tube, scatterer responses separated by down to 196 μm (or 1.05λ) were distinguished by the MV method, while the standard Delay-and-Sum (DAS) beamformers were unable to achieve such separation. Up to 9-fold FWHM decrease was also measured in favour of the MV beamformer, for individual echoes from MBs. The lateral distance between two scatterers impacted on their FWHM value, and additional differences in the scatterers' axial or out-of-plane position also impacted on their size and appearance. The simulation and experimental results were in agreement in terms of lateral resolution. The point scatterer study showed that the proposed MV imaging scheme provided clear resolution benefits compared to DAS. Current super-resolution methods mainly depend on DAS beamformers. Instead, the use of the MV method may provide a larger number of detected, and potentially better localized, MB scatterers.

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A comparison between temporal and subband minimum variance adaptive beamforming

Cited by 11 publications

References 18 publications

Understanding contrast improvements from capon beamforming

Understanding contrast improvements from capon beamforming

Super-Resolution Axial Localization of Ultrasound Scatter Using Multi-Focal Imaging

Resolving Ultrasound Contrast Microbubbles Using Minimum Variance Beamforming

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