1024-Channel 3D ultrasound digital beamformer in a single 5W FPGA

Angiolini, Federico; Ibrahim, Ahmed Mohamed Mahmoud; Simon, William; Yüzügüler, Ahmet Caner; Arditi, Marcel; Thiran, Jean‐Philippe; Micheli, Giovanni De

doi:10.23919/date.2017.7927175

Cited by 7 publications

(2 citation statements)

References 11 publications

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“…In medical ultrasound imaging, there are trends to support the point-of-care diagnosis outside of hospitals, such as in the home, at a patient's bedside, in the battlefield, and in the emergency room [1]. This framework necessitates ultracompact form factor instrumented on highly integrated circuit chip solutions: field programmable gated array (FPGA) and application-specific integrated chip (ASIC) [2]- [10]. Along with this trend towards point-of-care diagnosis, having a high frame rate have been desired to enable more advanced imaging features, that need to compound or analyze temporal changes of ultrasound signals [11]- [16].…”

Section: Introductionmentioning

confidence: 99%

Efficient Parallel-Beamforming Based on Shared FIFO for Ultra-Compact Ultrasound Imaging Systems

Kang¹,

Kim²,

Yoon³

et al. 2020

IEEE Access

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The realization of a parallel-beamforming (pBF) method in ultra-compact ultrasound imaging systems is challenging to achieve uncompromised beamforming accuracy in limited hardware and power resources. In this paper, we present a new hardware-and power-efficient pBF method that utilizes a shared first-in-first-out block on a post-fractional delay filtering architecture (pBF-sFIFO). For an analog-to-digital conversion (ADC) rate given, the proposed pBF-sFIFO method yielded beamforming accuracy comparable to that by an unconstrained pBF (pBF-CON) method, with up to 15% less power consumption. Otherwise, a conventional time-sharing pBF method (pBF-TS) was more vulnerable to aliasing artifacts. Even though increasing ADC rate in the pBF-TS method could recover the beamforming accuracy, exponential need in power consumption was inevitable. Therefore, the pBF-sFIFO method would be an effective solution to enable advanced imaging features in ultra-compact ultrasound imaging systems. INDEX TERMS Hardware complexity, parallel-beamforming, point-of-care, power consumption, ultracompact ultrasound imaging systems.

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Section: Introductionmentioning

confidence: 99%

Efficient Parallel-Beamforming Based on Shared FIFO for Ultra-Compact Ultrasound Imaging Systems

Kang¹,

Kim²,

Yoon³

et al. 2020

IEEE Access

View full text Add to dashboard Cite

show abstract

“…In high-definition 3-D ultrasound imaging, a large data set of received multichannel echo responses should be recorded for reconstructing each image line. Hardware-driven solutions exist where the full raw radio-frequency (RF) data are microbeamformed with dedicated electronic circuits on a matrix probe [6] or more recently, a low-consumption FPGA is programmed for beamforming up to 32×32 channels [7], [8]. For larger phased arrays, the necessary data bandwidth is increasing with the surface area of the transducer and now exceeds available resources for larger phased-array sensors.…”

mentioning

confidence: 99%

Ultrasound Imaging From Sparse RF Samples Using System Point Spread Functions

Schretter

Bundervoet

Blinder

et al. 2018

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

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Upcoming phased-array 2-D sensors will soon enable fast high-definition 3-D ultrasound imaging. Currently, the communication of raw radio-frequency (RF) channel data from the probe to the computer for digital beamforming is a bottleneck. For reducing the amount of transferred data samples, this paper investigates the design of an adapted sparse sampling technique for image reconstruction inspired by the compressed sensing framework. Echo responses from isolated points are generated using a physically based simulation of ultrasound wave propagation through tissues. These point spread functions form a dictionary of shift-variant bent waves, which depend on the specific sound excitation and acquisition protocols. Speckled ultrasound images can be approximately decomposed in this dictionary where sparsity is enforced at the system matrix design. The Moore-Penrose pseudoinverse is precomputed and used at the reconstruction stage for fast minimum-norm recovery from nonuniform pseudorandom sampled raw RF data. Results on simulated and acquired phantoms demonstrate the benefits of an optimized basis function design for high-quality B-mode image recovery from few RF channel data samples.

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EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging Without External Trackers

Khanal

Gómez

Toussaint

et al. 2018

Data Driven Treatment Response Assessment and Preterm, Perinatal, and Paediatric Image Analysis

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Ultrasound (US) is the most widely used fetal imaging technique. However, US images have limited capture range, and suffer from view dependent artefacts such as acoustic shadows. Compounding of overlapping 3D US acquisitions into a high-resolution volume can extend the field of view and remove image artefacts, which is useful for retrospective analysis including population based studies. However, such volume reconstructions require information about relative transformations between probe positions from which the individual volumes were acquired. In prenatal US scans, the fetus can move independently from the mother, making external trackers such as electromagnetic or optical tracking unable to track the motion between probe position and the moving fetus. We provide a novel methodology for image-based tracking and volume reconstruction by combining recent advances in deep learning and simultaneous localisation and mapping (SLAM). Tracking semantics are established through the use of a Residual 3D U-Net and the output is fed to the SLAM algorithm. As a proof of concept, experiments are conducted on US volumes taken from a whole body fetal phantom, and from the heads of real fetuses. For the fetal head segmentation, we also introduce a novel weak annotation approach to minimise the required manual effort for ground truth annotation. We evaluate our method qualitatively, and quantitatively with respect to tissue discrimination accuracy and tracking robustness.

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1024-Channel 3D ultrasound digital beamformer in a single 5W FPGA

Cited by 7 publications

References 11 publications

Efficient Parallel-Beamforming Based on Shared FIFO for Ultra-Compact Ultrasound Imaging Systems

Efficient Parallel-Beamforming Based on Shared FIFO for Ultra-Compact Ultrasound Imaging Systems

Ultrasound Imaging From Sparse RF Samples Using System Point Spread Functions

EchoFusion: Tracking and Reconstruction of Objects in 4D Freehand Ultrasound Imaging Without External Trackers

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