Updates on compositional MRI mapping of the cartilage: emerging techniques and applications
Osteoarthritis (OA) is a widely occurring degenerative joint disease that is severely
debilitating and causes significant socioeconomic burdens to society. Magnetic resonance …
debilitating and causes significant socioeconomic burdens to society. Magnetic resonance …
Accelerated cardiac diffusion tensor imaging using deep neural network
Cardiac diffusion tensor imaging (DTI) is a noninvasive method for measuring the
microstructure of the myocardium. However, its long scan time significantly hinders its wide …
microstructure of the myocardium. However, its long scan time significantly hinders its wide …
[HTML][HTML] Fast MRI Reconstruction Using Deep Learning-based Compressed Sensing: A Systematic Review
Magnetic resonance imaging (MRI) has revolutionized medical imaging, providing a non-
invasive and highly detailed look into the human body. However, the long acquisition times …
invasive and highly detailed look into the human body. However, the long acquisition times …
FlexDTI: flexible diffusion gradient encoding scheme-based highly efficient diffusion tensor imaging using deep learning
Z Wu, J Wang, Z Chen, Q Yang, Z Xing… - Physics in Medicine …, 2024 - iopscience.iop.org
Objective. Most deep neural network-based diffusion tensor imaging methods require the
diffusion gradients' number and directions in the data to be reconstructed to match those in …
diffusion gradients' number and directions in the data to be reconstructed to match those in …
An uncertainty aided framework for learning based liver T 1ρ mapping and analysis
Objective: Quantitative 𝑇1𝜌 imaging has potential for assessment of biochemical alterations
of liver pathologies. Deep learning methods have been employed to accelerate quantitative …
of liver pathologies. Deep learning methods have been employed to accelerate quantitative …
Improved quantitative parameter estimation for prostate T2 relaxometry using convolutional neural networks
Objective Quantitative parameter mapping conventionally relies on curve fitting techniques
to estimate parameters from magnetic resonance image series. This study compares …
to estimate parameters from magnetic resonance image series. This study compares …
Application of Variational Graph Autoencoder in Traction Control of Energy-Saving Driving for High-Speed Train
W Ma, J Wang, C Zhang, Q Jia, L Zhu, W Ji, Z Wang - Applied Sciences, 2024 - mdpi.com
In a high-speed rail system, the driver repeatedly adjusts the train's speed and traction while
driving, causing a high level of energy consumption. This also leads to the instability of the …
driving, causing a high level of energy consumption. This also leads to the instability of the …
Uncertainty-weighted Multi-tasking for T1ρ and T2 Mapping in the Liver with Self-supervised Learning
Multi-parametric mapping of MRI relaxations in liver has the potential of revealing
pathological information of the liver. A self-supervised learning based multi-parametric …
pathological information of the liver. A self-supervised learning based multi-parametric …