Enhanced pseudo-dynamic receive beamforming using focusing delay error compensation

Siritan, T.; Techavipoo, Udomchai; Worasawate, Denchai; Keinprasit, Rachaporn; Pinunsottikul, P.; Sugino, Nobuhiko; Thajchayapong, P.

doi:10.1109/bmeicon.2014.7017391

Cited by 1 publication

(2 citation statements)

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“…To solve this problem, a higher performance GPU is needed, e.g., a GPU with higher numbers of CUDA cores, such as 1536 or 3072 cores, which are already available in modern graphics cards. Rather than increase the CUDA cores, reducing the beamform dynamic focusing points [12] or applying pseudo-dynamic beamforming [13] could be an economic solution.…”

Section: Discussionmentioning

confidence: 99%

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Toward Optimal Computation of Ultrasound Image Reconstruction Using CPU and GPU

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et al. 2016

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An ultrasound image is reconstructed from echo signals received by array elements of a transducer. The time of flight of the echo depends on the distance between the focus to the array elements. The received echo signals have to be delayed to make their wave fronts and phase coherent before summing the signals. In digital beamforming, the delays are not always located at the sampled points. Generally, the values of the delayed signals are estimated by the values of the nearest samples. This method is fast and easy, however inaccurate. There are other methods available for increasing the accuracy of the delayed signals and, consequently, the quality of the beamformed signals; for example, the in-phase (I)/quadrature (Q) interpolation, which is more time consuming but provides more accurate values than the nearest samples. This paper compares the signals after dynamic receive beamforming, in which the echo signals are delayed using two methods, the nearest sample method and the I/Q interpolation method. The comparisons of the visual qualities of the reconstructed images and the qualities of the beamformed signals are reported. Moreover, the computational speeds of these methods are also optimized by reorganizing the data processing flow and by applying the graphics processing unit (GPU). The use of single and double precision floating-point formats of the intermediate data is also considered. The speeds with and without these optimizations are also compared.

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Section: Discussionmentioning

confidence: 99%

“…Because of using one focal point per window, other points in that window are out of focus. The out-of-focus delay error can be compensated using precomputed linear line approximation [13,14]. These methods are the so-called pseudo-dynamic receive beamforming.…”

Section: Introductionmentioning

confidence: 99%