Pixel-based approach to delay multiply and sum beamforming in combination with Wiener filter for improving ultrasound image quality

Guo, Hao; Xie, Hui-Wen; Zhou, Guang-Quan; Nguyen, Nghia Q.; Prager, Richard W.

doi:10.1016/j.ultras.2022.106864

Cited by 6 publications

(2 citation statements)

References 41 publications

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“…2) Noise characterization: By incorporating Wiener Filtering in the frequency domain, it is possible to target the removal of noise within specific frequency ranges [19]. Through Fourier Transform, we can obtain the spectral information of the signal and noise, including their power spectral densities and frequency distributions.…”

Section: Analysis Of the Advantages Of Combining Fourier Transform Andmentioning

confidence: 99%

Black Box Adversarial Defense Based on Image Denoising and Pix2Pix

Rui,

Gong

2023

JCC

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Deep Neural Networks (DNN) are widely utilized due to their outstanding performance, but the susceptibility to adversarial attacks poses significant security risks, making adversarial defense research crucial in the field of AI security. Currently, robustness defense techniques for models often rely on adversarial training, a method that tends to only defend against specific types of attacks and lacks strong generalization. In response to this challenge, this paper proposes a black-box defense method based on Image Denoising and Pix2Pix (IDP) technology. This method does not require prior knowledge of the specific attack type and eliminates the need for cumbersome adversarial training. When making predictions on unknown samples, the IDP method first undergoes denoising processing, followed by inputting the processed image into a trained Pix2Pix model for image transformation. Finally, the image generated by Pix2Pix is input into the classification model for prediction. This versatile defense approach demonstrates excellent defensive performance against common attack methods such as FGSM, I-FGSM, DeepFool, and UPSET, showcasing high flexibility and transferability. In summary, the IDP method introduces new perspectives and possibilities for adversarial sample defense, alleviating the limitations of traditional adversarial training methods and enhancing the overall robustness of models.

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Section: Analysis Of the Advantages Of Combining Fourier Transform Andmentioning

confidence: 99%

Black Box Adversarial Defense Based on Image Denoising and Pix2Pix

Rui,

Gong

2023

JCC

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“…As the echoes from the main lobe are received by arrays in different spatial locations, exhibiting higher similarity than the sidelobe. DMAS introduces the spatial coherence of different channel data by multiplicative coupling in the beamforming process, which preserves the main lobe and suppresses the clutter interference [26][27][28]. DMAS has been further improved as lagbased DMAS (L-DMAS) [29], subarray average DMAS (SA-DMAS) [30], double-stage DMAS (DS-DMAS) [31], baseband DMAS (BB-DMAS) [32], etc.…”

Section: Introductionmentioning

confidence: 99%

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Zhao,

Zhang,

Zhang

et al. 2024

Meas. Sci. Technol.

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High-resolution ultrasonic imaging for defects in anisotropic multilayer carbon fiber reinforced polymers (CFRPs) is challenging because of the severe ultrasonic attenuation and the low signal-to-noise ratio (SNR) of echoes. The existing delay-multiply-and-sum (DMAS) beamforming outperforms delay-and-sum (DAS) beamforming in resolution, but with high computational complexity and energy loss. This paper presents a novel delay-sum-and-square (DSAS) beamforming algorithm. It takes full advantage of spatial coherence of captured data in the receiving and transmitting apertures. The non-coherent components caused by background noise are suppressed during the imaging. The back-wall reflection method (BRM) is used to correct the direction-dependent velocity. Full-matrix data is experimentally captured and processed on three different CFRP samples. Compared with DAS and DMAS, DSAS has a significant improvement in resolution, SNR and contrast. It demonstrates excellent defect characterization and noise suppression capability with only 17.4% computation time of DMAS.

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Lamb wave imaging via dual-frequency fusion for grating lobe effect compensation

Gao,

Yang,

et al. 2025

Ultrasonics

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Pixel-based approach to delay multiply and sum beamforming in combination with Wiener filter for improving ultrasound image quality

Cited by 6 publications

References 41 publications

Black Box Adversarial Defense Based on Image Denoising and Pix2Pix

Black Box Adversarial Defense Based on Image Denoising and Pix2Pix

High-resolution defect imaging of composites using delay-sum-and-square beamforming algorithm

Lamb wave imaging via dual-frequency fusion for grating lobe effect compensation

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