1 citations · 1 across the 4 of their papers we have counts for
4 papers
Ultrafast Cardiac Imaging Using Deep Learning For Speckle-Tracking Echocardiography
Jingfeng Lu, Fabien Millioz, François Varray +5
High-quality ultrafast ultrasound imaging is based on coherent compounding from multiple transmissions of plane waves (PW) or diverging waves (DW). However, compounding results in…
High-quality Low-dose CT Reconstruction Using Convolutional Neural Networks with Spatial and Channel Squeeze and Excitation
Jingfeng Lu, Shuo Wang, Ping Li +1
Low-dose computed tomography (CT) allows the reduction of radiation risk in clinical applications at the expense of image quality, which deteriorates the diagnosis accuracy of radi…
Complex Convolutional Neural Networks for Ultrafast Ultrasound Image Reconstruction from In-Phase/Quadrature Signal
Jingfeng Lu, Fabien Millioz, Damien Garcia +3
Ultrafast ultrasound imaging remains an active area of interest in the ultrasound community due to its ultra-high frame rates. Recently, a wide variety of studies based on deep lea…
Reconstruction for Diverging-Wave Imaging Using Deep Convolutional Neural Networks
Jingfeng Lu, Fabien Millioz, Damien Garcia +3
In recent years, diverging-wave (DW) ultrasound imaging has become a very promising methodology for cardiovascular imaging due to its high temporal resolution. However, if they are…