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Found 6 papers, 1 papers with code
Phase Aberration Correction: A Deep Learning-Based Aberration to Aberration Approach
This dataset serves to mitigate the data scarcity problem in the development of deep learning-based techniques for phase aberration correction.
Deep Ultrasound Denoising Using Diffusion Probabilistic Models
To improve the Peak Signal to Noise Ratio (PSNR) of the images, previous denoising methods often remove the speckles, which could be informative for radiologists and also for quantitative ultrasound.
Inverse Problem of Ultrasound Beamforming with Denoising-Based Regularized Solutions
During the past few years, inverse problem formulations of ultrasound beamforming have attracted a growing interest.
Deep Ultrasound Denoising Without Clean Data
On one hand, the transmitted ultrasound beam gets attenuated as propagates through the tissue.
A Unifying Approach to Inverse Problems of Ultrasound Beamforming and Deconvolution
In parallel to beamforming approaches, deconvolution methods have also been explored in ultrasound imaging to mitigate the adverse effects of PSF.
Plane-Wave Ultrasound Beamforming: A Deep Learning Approach
Simulation test results confirm that the proposed method reconstructs images with a high quality in terms of resolution and contrast, which are also visually similar to the proposed ground-truth image.
