5 papers · 1 filter
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…
DeepAndes: A Self-Supervised Vision Foundation Model for Multi-Spectral Remote Sensing Imagery of the Andes
Junlin Guo, James R. Zimmer-Dauphinee, Jordan M. Nieusma +16
By mapping sites at large scales using remotely sensed data, archaeologists can generate unique insights into long-term demographic trends, inter-regional social networks, and past…
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…
Vision Foundation Models in Remote Sensing: A Survey
Siqi Lu, Junlin Guo, James R Zimmer-Dauphinee +5
Artificial Intelligence (AI) technologies have profoundly transformed the field of remote sensing, revolutionizing data collection, processing, and analysis. Traditionally reliant…