Strategies for Hardware Reduction on the Design of Portable Ultrasound Imaging Systems

Romero-Laorden, David; Villazón-Terrazas, Javier; Martínez-Graullera, Óscar; Ibanez, A.

doi:10.5772/55910

Cited by 6 publications

(3 citation statements)

References 11 publications

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“…The background behind CHEETAH library comes from the knowledge that our group has on beamforming acceleration using GPUs [5]- [7]. Nevertheless, it has been considered to briefly review the main concepts involved in the parallel implementation of the TFM process on the library.…”

Section: Parallel Gpu Implementationmentioning

confidence: 99%

“…The parallelization is performed launching as many threads as image pixels what, supposing image dimensions of S X × S Z , means N × S X × S Z threads. Several optimizations (reuse computed values, symmetries, shared/constant memories [7]) have been used to maximize performance. The focusing delay is calculated on-the-fly and it is indexed in the I(t) and Q(t) complex signals interpolating real and imaginary parts.…”

Section: Parallel Gpu Implementationmentioning

confidence: 99%

“…Some previous works as [2] show toolboxes for beamforming computation over CPUs and multi-core CPUs obtaining very good timing results. Our research group has been working on GPUs applied for field modeling acceleration [3] [4] as well as for fast beamforming [5]- [7] achieving speed ups of 150× over conventional CPU beamforming. Nowadays, GPU beamformers are a reality and there are lot of research groups working on solutions for NDT and medical applications [8].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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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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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Section: Parallel Gpu Implementationmentioning

confidence: 99%

Section: Parallel Gpu Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

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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Weighted non-linear beamformers for low cost 2-element receive ultrasound imaging system

Vayyeti

Thittai

2021

Ultrasonics

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LightProbe: A Digital Ultrasound Probe for Software-Defined Ultrafast Imaging

Hager

Benini

2019

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

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Digital ultrasound probes integrate the analog frontend in the housing of the probe handle and provide a digital interface instead of requiring an expensive coaxial cable harness to connect. Current digital probes target the portable market and perform the bulk of the processing (beamforming) on the probe, which enables the probe to be connected to commodity devices such as tablets or smartphones running an ultrasound app to display the image and control the probe. Thermal constraints limit the number of front-end channels as well as the complexity of the processing. This prevents current digital probes to support advanced modalities such as Vector Flow or Elastography requiring high-frame rate (HFR) imaging. In this paper, we present LIGHTPROBE, a digital ultrasound probe, which integrates a 64-channel 100 Vpp TX/RX frontend including analog-to-digital conversion (up to 32.5 MS/s @ 12 bit), and is equipped with an optical high-speed link (26.4 Gb/s) providing sustainable raw samples access to all channels, which allows the processing to be performed on the connected device without thermal power constraints. By connecting the probe to a GPU-equipped PC, we demonstrate the flexibility of softwaredefined B-mode imaging using conventional and ultrafast methods. We achieve plane-wave and synthetic aperture imaging with frame-rates from 30 Hz up to 500 Hz consuming between 5.6 W and 10.7 W. By using a combination of power and thermal management techniques, we demonstrate that the probe can remain within operating temperature limits even without active cooling, while never having to turn the probe off for cooling hence providing a consistent Quality of Service for the operator.

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Strategies for Hardware Reduction on the Design of Portable Ultrasound Imaging Systems

Cited by 6 publications

References 11 publications

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

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

Weighted non-linear beamformers for low cost 2-element receive ultrasound imaging system

LightProbe: A Digital Ultrasound Probe for Software-Defined Ultrafast Imaging

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