In this article, two novel deep learning methods are proposed for displacement estimation in
ultrasound elastography (USE). Although convolutional neural networks (CNNs) have been …

Many of the current techniques in transient elastography, such as shear wave elastography
(SWE) assume a dominant planar shear wave propagating in an infinite medium. This …

In quasi-static ultrasound elastography, breast tumor classification can be performed by
using the rotation fill-in signature present in the rotation elastogram. This rotation fill-in …

Acoustoelasticity (AE) aims at measuring the elastic nonlinearity of a medium based on the
evolution of its shear wave speed as the medium is uniaxially stressed. In the field of …

Ultrasound data often suffers from an excessive amount of noise especially from deep tissue
or in synthetic aperture imaging where the acoustic wave is weak. Such noisy data renders …

Elastography involves tracking the ultrasonic A-mode signals before and after mechanical
compression of tissue to form a computed image of the local strains undergone by various …

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 …

Ultrasound shear wave elasticity imaging is a valuable tool for quantifying the elastic
properties of tissue. Typically, the shear wave velocity is derived and mapped to an elasticity …

Medical imaging is vital to modern clinical practice, enabling clinicians to examine tissues
inside the human body non-invasively. Its value depends on accuracy, resolution, and the …

Ultrasound strain imaging is becoming increasingly popular as a way to measure stiffness
variation in soft tissue. Almost all techniques involve the estimation of a field of relative …