2 citations · 4 across the 7 of their papers we have counts for
7 papers
An artificially intelligent magnetic resonance spectroscopy quantification method: Comparison between QNet and LCModel on the cloud computing platform CloudBrain-MRS
Meijin Lin, Lin Guo, Dicheng Chen +10
Objctives: This work aimed to statistically compare the metabolite quantification of human brain magnetic resonance spectroscopy (MRS) between the deep learning method QNet and the…
CloudBrain-MRS: An Intelligent Cloud Computing Platform for in vivo Magnetic Resonance Spectroscopy Preprocessing, Quantification, and Analysis
Xiaodie Chen, Jiayu Li, Dicheng Chen +13
Magnetic resonance spectroscopy (MRS) is an important clinical imaging method for diagnosis of diseases. MRS spectrum is used to observe the signal intensity of metabolites or furt…
Magnetic Resonance Spectroscopy Quantification Aided by Deep Estimations of Imperfection Factors and Macromolecular Signal
Dicheng Chen, Meijin Lin, Huiting Liu +11
Objective: Magnetic Resonance Spectroscopy (MRS) is an important technique for biomedical detection. However, it is challenging to accurately quantify metabolites with proton MRS d…
A Dynamics Theory of Implicit Regularization in Deep Low-Rank Matrix Factorization
Jian Cao, Chen Qian, Yihui Huang +5
Implicit regularization is an important way to interpret neural networks. Recent theory starts to explain implicit regularization with the model of deep matrix factorization (DMF)…
Magnetic Resonance Spectroscopy Deep Learning Denoising Using Few In Vivo Data
Dicheng Chen, Wanqi Hu, Huiting Liu +13
Magnetic Resonance Spectroscopy (MRS) is a noninvasive tool to reveal metabolic information. One challenge of 1H-MRS is the low Signal-Noise Ratio (SNR). To improve the SNR, a typi…
Spatiotemporal Flexible Sparse Reconstruction for Rapid Dynamic Contrast-enhanced MRI
Yuhan Hu, Xinlin Zhang, Li Feng +6
Dynamic Contrast-enhanced magnetic resonance imaging (DCE-MRI) is a tissue perfusion imaging technique. Some versatile free-breathing DCE-MRI techniques combining compressed sensin…
Review and Prospect: Deep Learning in Nuclear Magnetic Resonance Spectroscopy
Dicheng Chen, Zi Wang, Di Guo +2
Since the concept of Deep Learning (DL) was formally proposed in 2006, it had a major impact on academic research and industry. Nowadays, DL provides an unprecedented way to analyz…