1 citations · 1 across the 5 of their papers we have counts for
6 papers
OpenMASC: An Open-Source Pipeline for Cross-Trajectory Metal-Aware Sampling and Correction in Accelerated MRI
Zhengyi Lu, Ming Lu, Chongyu Qu +11
Metal implants corrupt MRI measurements throughout -space, yet existing accelerated MRI methods assume clean data and most metal artifact reduction approaches assume fully sampl…
MASC: Metal-Aware Sampling and Correction via Reinforcement Learning for Accelerated MRI
Zhengyi Lu, Ming Lu, Chongyu Qu +11
Metal implants in MRI cause severe artifacts that degrade image quality and hinder clinical diagnosis. Traditional approaches address metal artifact reduction (MAR) and accelerated…
Sparse Measurement Medical CT Reconstruction using Multi-Fused Block Matching Denoising Priors
Maliha Hossain, Yuankai Huo, Xinqiang Yan +1
A major challenge for medical X-ray CT imaging is reducing the number of X-ray projections to lower radiation dosage and reduce scan times without compromising image quality. Howev…
Fast-RF-Shimming: Accelerate RF Shimming in 7T MRI using Deep Learning
Zhengyi Lu, Hao Liang, Ming Lu +3
Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) offers an elevated signal-to-noise ratio (SNR), enabling exceptionally high spatial resolution that benefits both clinical di…
Optimizing Transmit Field Inhomogeneity of Parallel RF Transmit Design in 7T MRI using Deep Learning
Zhengyi Lu, Hao Liang, Xiao Wang +2
Ultrahigh field (UHF) Magnetic Resonance Imaging (MRI) provides a higher signal-to-noise ratio and, thereby, higher spatial resolution. However, UHF MRI introduces challenges such…
On the Equivalence of Demagnetization Tensors as Discrete Cell Size Approaches Zero in Three-Dimensional Space
Hao Liang, Xinqiang Yan
The calculation of the demagnetization field is crucial in various disciplines, including magnetic resonance imaging (MRI) and micromagnetics. A standard method involves discretizi…