Medical & Biological Engineering & Computing

, Volume 57, Issue 12, pp 2717–2729 | Cite as

Combining autocorrelation signals with delay multiply and sum beamforming algorithm for ultrasound imaging

  • Ke SongEmail author
  • Paul Liu
  • Dong C. Liu
Original Article


Beamformer is one of the most important components in ultrasound imaging system. The delay and sum (DAS) beamforming algorithm has been widely used in recent decades due to its simplicity and robustness. However, it has poor impact on resolution and contrast. A new beamformer named filtered delay multiply and sum (F-DMAS) which was an alternative of delay multiply and sum (DMAS) was proposed to overcome these shortcomings of DAS. Although F-DMAS partially enhances the image quality, its performance still has room for improvement. Therefore, a novel beamformer named lag-based delay multiply and sum (L-DMAS) which combines autocorrelation signals with DMAS algorithm is proposed by us to improve its efficiency. Field II was employed to synthesize a point target phantom and a cyst phantom to compare the performance between DAS, F-DMAS, double stage delay multiply and sum (DS-DMAS), and L-DMAS. We also estimate the performance of four algorithms on experimental data and in vivo data. These results show that both DS-DMAS and L-DMAS are better than DAS and F-DMAS in each case. In some cases, DS-DMAS and L-DMAS have little difference in performance, but in other cases, L-DMAS outperforms DS-DMAS.

Graphical Abstract


Ultrasound imaging Beamforming Autocorrelation Lag Delay multiply and sum 



The authors would like to thank the reviewers for their valuable comments and suggestions. We also thank Saset Healthcare (Chengdu) Inc., for providing the ultrasound device.

Funding information

This work is partially supported by the Science and Technology Research Program of Chongqing Municipal Education Commission (Grant No KJQN201801606), in part by Chongqing Electronics Engineering Technology Research Center for Interactive Learning, and in part by Chongqing Big Data Engineering Laboratory for Children.


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Copyright information

© International Federation for Medical and Biological Engineering 2019

Authors and Affiliations

  1. 1.College of Computer ScienceSichuan UniversityChengduChina
  2. 2.School of Mathematics and Information EngineeringChongqing University of EducationChongqingChina
  3. 3.Stork Healthcare Ltd.ChengduChina

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