An adaptive beamforming method for ultrasound imaging based on the mean-to-standard-deviation factor

Wang, Yuanguo; Zheng, Cao; Peng, Hu; Chen, Qiang

doi:10.1016/j.ultras.2018.06.006

Cited by 46 publications

(13 citation statements)

References 48 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…( 1 ), CF of a perfectly coherent signal will be 1, and that of a perfectly incoherent signal will be 0. To further increase the difference between coherent and incoherent signals, the mean-to-standard-deviation (MSD) factor [ 14 ] and signal-to-noise-ratio (SNR) factor [ 15 ] were introduced. The CF value for a perfectly coherent signal is limited to 1 because CF is defined as the ratio of coherent energy to “total energy”.…”

Section: Adaptive Imaging Methodsmentioning

confidence: 99%

Advances in ultrasonography: image formation and quality assessment

Hasegawa

2021

J Med Ultrasonics

View full text Add to dashboard Cite

Delay-and-sum (DAS) beamforming is widely used for generation of B-mode images from echo signals obtained with an array probe composed of transducer elements. However, the resolution and contrast achieved with DAS beamforming are determined by the physical specifications of the array, e.g., size and pitch of elements. To overcome this limitation, adaptive imaging methods have recently been explored extensively thanks to the dissemination of digital and programmable ultrasound systems. On the other hand, it is also important to evaluate the performance of such adaptive imaging methods quantitatively to validate whether the modification of the image characteristics resulting from the developed method is appropriate. Since many adaptive imaging methods have been developed and they often alter image characteristics, attempts have also been made to update the methods for quantitative assessment of image quality. This article provides a review of recent developments in adaptive imaging and image quality assessment.

show abstract

Section: Adaptive Imaging Methodsmentioning

confidence: 99%

Advances in ultrasonography: image formation and quality assessment

Hasegawa

2021

J Med Ultrasonics

View full text Add to dashboard Cite

show abstract

“…Standard deviation (SD) is a statistical concept, which has been widely used in many fields. Such as in [33], standard deviation was used into industrial equipment to help process the signal of bubble detection in liquid sodium; in [34], standard deviation is used with delay multiply to form a new weighting factor, which is introduced to enhance the contrast of the reconstructed images in medical fields; in [35], based on eight-year-old dental trauma research data, standard deviation was utilized to help analyze the potential of laser Doppler flowmetry; the beam forming performance has a large impact on image quality in ultrasound imaging, to improve image resolution and contrast; in [36], a new adaptive weighting factor for ultrasound imaging called signal mean-to-standard-deviation factor (SMSF) was proposed, based on which researchers put forward an adaptive beam forming method for ultrasound imaging based on the mean-to-standard-deviation factor; in [37], standard deviation was adopted to help analyze when an individual should start social security.…”

Section: Standard Deviation Updating Amount (Sdua)mentioning

confidence: 99%

An Adaptive Shrinking Grid Search Chaotic Wolf Optimization Algorithm Using Standard Deviation Updating Amount

Wang

Ban

et al. 2020

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

To improve the optimization quality, stability, and speed of convergence of wolf pack algorithm, an adaptive shrinking grid search chaotic wolf optimization algorithm using standard deviation updating amount (ASGS-CWOA) was proposed. First of all, a strategy of adaptive shrinking grid search (ASGS) was designed for wolf pack algorithm to enhance its searching capability through which all wolves in the pack are allowed to compete as the leader wolf in order to improve the probability of finding the global optimization. Furthermore, opposite-middle raid method (OMR) is used in the wolf pack algorithm to accelerate its convergence rate. Finally, “Standard Deviation Updating Amount” (SDUA) is adopted for the process of population regeneration, aimed at enhancing biodiversity of the population. The experimental results indicate that compared with traditional genetic algorithm (GA), particle swarm optimization (PSO), leading wolf pack algorithm (LWPS), and chaos wolf optimization algorithm (CWOA), ASGS-CWOA has a faster convergence speed, better global search accuracy, and high robustness under the same conditions.

show abstract

“…Cross coherence factor was devised by combing plane-and spherical-wave transmissions to reduce artifact caused by sidelobes in ultrafast ultrasound imaging [26]. A normalized autocorrelation factor was proposed for coherent planewave compounding to enhance lateral resolution and contrast [27]. Eigenspace-based coherence factor was presented to improve tissue harmonic imaging to achieve high resolution and good small target visibility at the same time [28].…”

Section: Introductionmentioning

confidence: 99%

Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study

Zheng¹,

Wang²,

Wang³

et al. 2022

Computer Modeling in Engineering &Amp; Sciences

Self Cite

View full text Add to dashboard Cite

Virtual source (VS) imaging has been proposed to improve image resolution in medical ultrasound imaging. However, VS obtains a limited contrast due to the non-adaptive delay-and-sum (DAS) beamforming. To improve the image contrast and provide an enhanced resolution, adaptive weighting algorithms were applied in VS imaging. In this paper, we proposed an adjustable generalized coherence factor (aGCF) for the synthetic aperture sequential beamforming (SASB) of VS imaging to improve image quality. The value of aGCF is adjusted by a sequence intensity factor (SIF) that is defined as the ratio between the effective low resolution scan lines (LRLs) intensity and total LRLs strength. The aGCF-weighted VS (aGCF-VS) images were compared with standard VS images and GCF-weighted VS (GCF-VS) images. Simulation and experimental results demonstrated that the contrast ratio (CR) and contrastto-noise ratio (CNR) of aGCF-VS are greatly improved, compared with standard VS imaging. And in comparison with GCF-VS, aGCF-VS can obtain better CNR and speckle signal-to-noise ratio (sSNR) while maintaining similar CR. Therefore, aGCF is suitable for VS imaging to improve contrast and preserve speckle pattern.

show abstract

An adaptive beamforming method for ultrasound imaging based on the mean-to-standard-deviation factor

Cited by 46 publications

References 48 publications

Advances in ultrasonography: image formation and quality assessment

Advances in ultrasonography: image formation and quality assessment

An Adaptive Shrinking Grid Search Chaotic Wolf Optimization Algorithm Using Standard Deviation Updating Amount

Adaptive Virtual Source Imaging Using the Sequence Intensity Factor: Simulation and Experimental Study

Contact Info

Product

Resources

About