Unveiling the future of breast cancer assessment: a critical review on generative adversarial networks in elastography ultrasound

MY Ansari, M Qaraqe, R Righetti, E Serpedin… - Frontiers in …, 2023 - frontiersin.org
Elastography Ultrasound provides elasticity information of the tissues, which is crucial for
understanding the density and texture, allowing for the diagnosis of different medical …

Deep learning in ultrasound elastography imaging: A review

H Li, M Bhatt, Z Qu, S Zhang, MC Hartel… - Medical …, 2022 - Wiley Online Library
It is known that changes in the mechanical properties of tissues are associated with the
onset and progression of certain diseases. Ultrasound elastography is a technique to …

Unsupervised convolutional neural network for motion estimation in ultrasound elastography

X Wei, Y Wang, L Ge, B Peng, Q He… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
High-quality motion estimation is essential for ultrasound elastography (USE). Traditional
motion estimation algorithms based on speckle tracking such as normalized cross …

Displacement Tracking Techniques in Ultrasound Elastography: From Cross-Correlation to Deep Learning

M Ashikuzzaman, A Héroux, A Tang… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
Ultrasound elastography is a non-invasive medical imaging technique that maps
viscoelastic properties to characterize tissues and diseases. Elastography can be divided …

Displacement-based reconstruction of elasticity distribution with deep neural network

X Zhang, R Wang, X Wei, J Luo… - 2022 IEEE International …, 2022 - ieeexplore.ieee.org
Reconstructing tissue elasticity distribution is an ill-posed inverse problem in ultrasound
elastography. Conventional methods usually require too much iterative computation and …

Ultrasound Despeckling With GANs and Cross Modality Transfer Learning

DF Vieira, A Raposo, A Azeitona, M Afonso… - IEEE …, 2024 - ieeexplore.ieee.org
Ultrasound images are corrupted by a type of signal-dependent noise, called speckle,
difficult to remove or attenuate with the classical denoising methods. On the contrary …

Super-resolution techniques for biomedical applications and challenges

M Shin, M Seo, K Lee, K Yoon - Biomedical Engineering Letters, 2024 - Springer
Super-resolution (SR) techniques have revolutionized the field of biomedical applications by
detailing the structures at resolutions beyond the limits of imaging or measuring tools. These …

Adaptive data function for robust ultrasound elastography

M Ashikuzzaman, TJ Hall… - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Regularized optimization-based ultrasound elastography techniques minimize an energy
function consisting of data and continuity terms to obtain the displacement tensor between …

[HTML][HTML] 基于半监督神经网络的弹性模量分布重建

潇张, 博彭, 锐王, 星月魏, 建文罗 - … Wu Yi Xue Gong Cheng Xue …, 2024 - ncbi.nlm.nih.gov
在超声弹性成像中, 准确重建组织弹性模量分布是一项重要挑战。 现有的基于深度学习的全
监督重建方法在训练中只使用了添加噪声的计算机仿真位移数据, 不能完全模拟在体超声数据 …

Performance Assessment of Motion Tracking Methods in Ultrasound-based Shear Wave Elastography

T He, B Peng, P Chen, J Jiang - 2020 IEEE International …, 2020 - ieeexplore.ieee.org
Ultrasound elastography is a modality that is uniquely suited to augment conventional B-
mode ultrasound for various clinical applications. Motion tracking plays a critically important …