Deep learning for image enhancement and correction in magnetic resonance imaging—state-of-the-art and challenges
Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical
diagnoses and research which underpin many recent breakthroughs in medicine and …
diagnoses and research which underpin many recent breakthroughs in medicine and …
[HTML][HTML] What's new and what's next in diffusion MRI preprocessing
Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …
Map** the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact
Tremendous efforts have been made in the last decade to advance cutting-edge MRI
technology in pursuit of map** structural connectivity in the living human brain with …
technology in pursuit of map** structural connectivity in the living human brain with …
Pushing the limits of low‐cost ultra‐low‐field MRI by dual‐acquisition deep learning 3D superresolution
Purpose Recent development of ultra‐low‐field (ULF) MRI presents opportunities for low‐
power, shielding‐free, and portable clinical applications at a fraction of the cost. However, its …
power, shielding‐free, and portable clinical applications at a fraction of the cost. However, its …
Tensor denoising of multidimensional MRI data
Purpose To develop a denoising strategy leveraging redundancy in high‐dimensional data.
Theory and Methods The SNR fundamentally limits the information accessible by MRI. This …
Theory and Methods The SNR fundamentally limits the information accessible by MRI. This …
[HTML][HTML] Nonparametric D-R1-R2 distribution MRI of the living human brain
Diffusion-relaxation correlation NMR can simultaneously characterize both the
microstructure and the local chemical composition of complex samples that contain multiple …
microstructure and the local chemical composition of complex samples that contain multiple …
A review of deep learning methods for compressed sensing image reconstruction and its medical applications
Compressed sensing (CS) and its medical applications are active areas of research. In this
paper, we review recent works using deep learning method to solve CS problem for images …
paper, we review recent works using deep learning method to solve CS problem for images …