Coherent Bistatic 3-D Ultrasound Imaging Using Two Sparse Matrix Arrays

Hoop, Hein de; Schwab, Hans-Martin; Lopata, R.G.P.

doi:10.1109/tuffc.2022.3233158

Cited by 6 publications

(3 citation statements)

References 45 publications

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“…These developments could in the future also contribute towards semi-tomographic ultrasound approaches that can cover a large FOV, for instance using wearable ultrasound patches ( Lin et al, 2023 ). 3-D bistatic ultrasound imaging using two sparse matrix arrays has recently been proven feasible in an ex vivo study ( De Hoop et al, 2022 ). This removes the limitation of scanning in the same imaging plane and can capture out-of-plane motion.…”

Section: Discussionmentioning

confidence: 99%

In vivo bistatic dual-aperture ultrasound imaging and elastography of the abdominal aorta

van Hal,

de Hoop,

van Sambeek

et al. 2024

Front. Physiol.

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Introduction: In this paper we introduce in vivo multi-aperture ultrasound imaging and elastography of the abdominal aorta. Monitoring of the geometry and growth of abdominal aortic aneurysms (AAA) is paramount for risk stratification and intervention planning. However, such an assessment is limited by the lateral lumen-wall contrast and resolution of conventional ultrasound. Here, an in vivo dual-aperture bistatic imaging approach is shown to improve abdominal ultrasound and strain imaging quality significantly. By scanning the aorta from different directions, a larger part of the vessel circumference can be visualized.Methods: In this first-in-man volunteer study, the performance of multi-aperture ultrasound imaging and elastography of the abdominal aortic wall was assessed in 20 healthy volunteers. Dual-probe acquisition was performed in which two curved array transducers were aligned in the same imaging plane. The transducers alternately transmit and both probes receive simultaneously on each transmit event, which allows for the reconstruction of four ultrasound signals. Automatic probe localization was achieved by optimizing the coherence of the trans-probe data, using a gradient descent algorithm. Speckle-tracking was performed on the four individual bistatic signals, after which the respective axial displacements were compounded and strains were calculated.Results: Using bistatic multi-aperture ultrasound imaging, the image quality of the ultrasound images, i.e., the angular coverage of the wall, was improved which enables accurate estimation of local motion dynamics and strain in the abdominal aortic wall. The motion tracking error was reduced from 1.3 mm ± 0.63 mm to 0.16 mm ± 0.076 mm, which increased the circumferential elastographic signal-to-noise ratio (SNRe) by 12.3 dB ± 8.3 dB on average, revealing more accurate and homogeneous strain estimates compared to single-perspective ultrasound.Conclusion: Multi-aperture ultrasound imaging and elastography is feasible in vivo and can provide the clinician with vital information about the anatomical and mechanical state of AAAs in the future.

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Section: Discussionmentioning

confidence: 99%

In vivo bistatic dual-aperture ultrasound imaging and elastography of the abdominal aorta

van Hal,

de Hoop,

van Sambeek

et al. 2024

Front. Physiol.

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“…This remains a challenge, with US quality being limited by the use of time-resolved data (lower spatial resolution), abdominal fat (less US signal reaching the AAA) and bowel gas (shadow artifacts). Other limitations of US could be overcome with new US techniques, such as multi-aperture US imaging, combining proximal and distal images to increase the field-of-view [23] or combining images from different angles to improve the visibility of the whole AAA circumference [24]. With improvement of the image quality, segmentation performance is expected to improve, also at the proximal and distal ends.…”

Section: Discussionmentioning

confidence: 99%

Automatic Segmentation of Abdominal Aortic Aneurysms from Time-Resolved 3D Ultrasound Images Using Deep Learning

Maas,

Awasthi,

Van Pelt

et al. 2024

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

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Abdominal aortic aneurysms (AAAs) are rupture-prone dilatations of the aorta. In current clinical practice, the maximal diameter of AAAs is monitored with 2D ultrasound to estimate their rupture risk. Recent studies have shown that 3-dimensional and mechanical AAA parameters might be better predictors for aneurysm growth and rupture than the diameter. These parameters can be obtained with time-resolved 3D ultrasound (3D+t US), which requires robust and automatic segmentation of AAAs from 3D+t US. This study proposes and validates a deep learning (DL) approach for automatic segmentation of AAAs. 500 AAA patients were included for follow-up 3D+t US imaging, resulting in 2495 3D+t US images. Segmentation masks for model training were obtained using a conventional automatic segmentation algorithm ('nonDL'). Four different DL models were trained and validated by (1) comparison to CT and (2) reader scoring. Performance of the nonDL and different DL segmentation strategies were evaluated by comparing Hausdorff distance, Dice scores, accuracy, sensitivity, and specificity with a sign test. All DL models had higher median Dice scores, accuracy, and sensitivity (all p < 0.003) compared to nonDL segmentation. The full image-resolution model without data augmentation showed the highest median Dice score and sensitivity (p < 0.001). Applying the DL model on an independent test group produced fewer poor segmentation scores of 1 to 2 on a five-point scale (8% for DL, 18% for nonDL). This demonstrates that a robust and automatic segmentation algorithm for segmenting abdominal aortic aneurysms from 3D+t US images was developed, showing improved performance compared to conventional segmentation.

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“…Coherent combination of all signals received by the extended aperture improves resolution and sensitivity, and extends the FOV, while flexible placement of individual arrays preserves compatibility with different body shapes and parallel operation can preserve time resolution. In contrast to previous works on multiple probes that rely on a fixed geometry [12][13][14][15], CoMTUS utilizes multiple standard US arrays that can be positioned flexibly and combined into an extended dynamically self-calibrating large aperture. This calibration is done by optimizing the beamforming parameters: the average sound speed in the medium, and the location of the transducers [11].…”

Section: Of 15mentioning

confidence: 99%

On the Arrays Distribution, Scan Sequence and Apodization in Coherent Dual-Array Ultrasound Imaging Systems

Peralta,

Mazierli,

Christensen-Jeffries

et al. 2023

Applied Sciences

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Coherent multi-transducer ultrasound (CoMTUS) imaging creates an extended effective aperture through the coherent combination of multiple arrays, which results in images with enhanced resolution, extended field-of-view, and higher sensitivity. However, this also creates a large discontinuous effective aperture that presents additional challenges for current beamforming methods. The discontinuities may increase the level of grating and side lobes and degrade contrast. Also, direct transmissions between multiple arrays, happening at certain transducer relative positions, produce undesirable cross-talk artifacts. Hence, the position of the transducers and the scan sequence play key roles in the beamforming algorithm and imaging performance of CoMTUS. This work investigates the role of the distribution of the individual arrays and the scan sequence in the imaging performance of a coherent dual-array system. First, the imaging performance for different configurations was assessed numerically using the point-spread-function, and then optimized settings were tested on a tissue mimicking phantom. Finally, a subset of the proposed optimum imaging schemes was experimentally validated on two synchronized ULA OP-256 systems equipped with identical linear arrays. Results show that CoMTUS imaging performance can be enhanced by optimizing the relative position of the arrays and the scan sequence together, and that the use of apodization can reduce cross-talk artifacts without degrading spatial resolution. Adding weighted compounding further decreases artifacts and helps to compensate for the differences in the brightness across the image. Setting the maximum steering angle according to the spatial configuration of the arrays reduces the sidelobe energy up to 10 dB plus an extra 4 dB reduction is possible when increasing the number of PWs compounded.

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Coherent Bistatic 3-D Ultrasound Imaging Using Two Sparse Matrix Arrays

Cited by 6 publications

References 45 publications

In vivo bistatic dual-aperture ultrasound imaging and elastography of the abdominal aorta

In vivo bistatic dual-aperture ultrasound imaging and elastography of the abdominal aorta

Automatic Segmentation of Abdominal Aortic Aneurysms from Time-Resolved 3D Ultrasound Images Using Deep Learning

On the Arrays Distribution, Scan Sequence and Apodization in Coherent Dual-Array Ultrasound Imaging Systems

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