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CloudBrain-MRS: An Intelligent Cloud Computing Platform for in vivo Magnetic Resonance Spectroscopy Preprocessing, Quantification, and Analysis
We have shared our cloud platform at MRSHub, providing free access and service for two years.
Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal
Methods: Linear Least Squares (LLS) is integrated with deep learning to reduce the complexity of solving this overall quantification.
A Dynamics Theory of Implicit Regularization in Deep Low-Rank Matrix Factorization
Recent theory starts to explain implicit regularization with the model of deep matrix factorization (DMF) and analyze the trajectory of discrete gradient dynamics in the optimization process.
Magnetic Resonance Spectroscopy Deep Learning Denoising Using Few In Vivo Data
A deep learning model, Refusion Long Short-Term Memory (ReLSTM), was designed to learn the mapping from the low SNR time-domain data (24 SA) to the high SNR one (128 SA).
Review and Prospect: Deep Learning in Nuclear Magnetic Resonance Spectroscopy
In this Minireview, we summarize applications of DL in Nuclear Magnetic Resonance (NMR) spectroscopy and outline a perspective for DL as entirely new approaches that are likely to transform NMR spectroscopy into a much more efficient and powerful technique in chemistry and life science.
