78 citations · 159 across the 3 of their papers we have counts for
6 papers
Training Variational Networks with Multi-Domain Simulations: Speed-of-Sound Image Reconstruction
Melanie Bernhardt, Valery Vishnevskiy, Richard Rau +1
Speed-of-sound has been shown as a potential biomarker for breast cancer imaging, successfully differentiating malignant tumors from benign ones. Speed-of-sound images can be recon…
Deep Network for Scatterer Distribution Estimation for Ultrasound Image Simulation
Lin Zhang, Valery Vishnevskiy, Orcun Goksel
Simulation-based ultrasound training can be an essential educational tool. Realistic ultrasound image appearance with typical speckle texture can be modeled as convolution of a poi…
Deep variational network for rapid 4D flow MRI reconstruction
Valery Vishnevskiy, Jonas Walheim, Sebastian Kozerke
Phase-contrast magnetic resonance imaging (MRI) provides time-resolved quantification of blood flow dynamics that can aid clinical diagnosis. Long in vivo scan times due to repeate…
Frequency-Dependent Attenuation Reconstruction with an Acoustic Reflector
Richard Rau, Ozan Unal, Dieter Schweizer +2
Attenuation of ultrasound waves varies with tissue composition, hence its estimation offers great potential for tissue characterization and diagnosis and staging of pathology. We r…
Ultrasound Aberration Correction based on Local Speed-of-Sound Map Estimation
Richard Rau, Dieter Schweizer, Valery Vishnevskiy +1
For beamforming ultrasound (US) signals, typically a spatially constant speed-of-sound (SoS) is assumed to calculate delays. As SoS in tissue may vary relatively largely, this appr…
Attenuation Imaging with Pulse-Echo Ultrasound based on an Acoustic Reflector
Richard Rau, Ozan Unal, Dieter Schweizer +2
Ultrasound attenuation is caused by absorption and scattering in tissue and is thus a function of tissue composition, hence its imaging offers great potential for screening and dif…