Literature DB >> 33360053

So you think you can DAS? A viewpoint on delay-and-sum beamforming.

Vincent Perrot1, Maxime Polichetti1, François Varray1, Damien Garcia2.   

Abstract

Delay-and-sum (DAS) is the most widespread digital beamformer in high-frame-rate ultrasound imaging. Its implementation is simple and compatible with real-time applications. In this viewpoint article, we describe the fundamentals of DAS beamforming. The underlying theory and numerical approach are detailed so that users can be aware of its functioning and limitations. In particular, we discuss the importance of the f-number and speed of sound on image quality, and propose one solution to set their values from a physical viewpoint. We suggest determining the f-number from the directivity of the transducer elements and the speed of sound from the phase dispersion of the delayed signals. Simplified Matlab codes are provided for the sake of clarity and openness. The effect of the f-number and speed of sound on the lateral resolution and contrast-to-noise ratio was investigated in vitro and in vivo. If not properly preset, these two factors had a substantial negative impact on standard metrics of image quality (namely CNR and FWHM). When beamforming with DAS in vitro or in vivo, it is recommended to optimize these parameters in order to use it wisely and prevent image degradation.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Beamforming; Delay-and-sum; Speed of sound; f-number

Year:  2020        PMID: 33360053     DOI: 10.1016/j.ultras.2020.106309

Source DB:  PubMed          Journal:  Ultrasonics        ISSN: 0041-624X            Impact factor:   2.890


  3 in total

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Authors:  Rajat Suvra Halder; Ashish Sahani
Journal:  Phys Eng Sci Med       Date:  2022-09-29

2.  Minimum variance beamforming combined with covariance matrix-based adaptive weighting for medical ultrasound imaging.

Authors:  Yuanguo Wang; Yadan Wang; Mingzhou Liu; Zhengfeng Lan; Chichao Zheng; Hu Peng
Journal:  Biomed Eng Online       Date:  2022-06-18       Impact factor: 3.903

3.  Deep Learning for Ultrasound Image Formation: CUBDL Evaluation Framework and Open Datasets.

Authors:  Dongwoon Hyun; Alycen Wiacek; Sobhan Goudarzi; Sven Rothlubbers; Amir Asif; Klaus Eickel; Yonina C Eldar; Jiaqi Huang; Massimo Mischi; Hassan Rivaz; David Sinden; Ruud J G van Sloun; Hannah Strohm; Muyinatu A Lediju Bell
Journal:  IEEE Trans Ultrason Ferroelectr Freq Control       Date:  2021-11-23       Impact factor: 2.725

  3 in total

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