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MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping [article]

Ruimin Feng, Jiayi Zhao, He Wang, Baofeng Yang, Jie Feng, Yuting Shi, Ming Zhang, Chunlei Liu, Yuyao Zhang, Jie Zhuang, Hongjiang Wei
2021 arXiv   pre-print
In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM.  ...  Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases.  ...  Discussion In this study, we proposed a model-based generative adversarial deep learning network for quantitative susceptibility mapping.  ... 
arXiv:2101.08413v2 fatcat:2pq6zm4l2bfuhisnganstjylii

MoDL-QSM: Model-based Deep Learning for Quantitative Susceptibility Mapping

Ruimin Feng, Jiayi Zhao, He Wang, Baofeng Yang, Jie Feng, Yuting Shi, Ming Zhang, Chunlei Liu, Yuyao Zhang, Jie Zhuang, Hongjiang Wei
2021 NeuroImage  
In this study, we proposed a model-based deep learning architecture that followed the STI (susceptibility tensor imaging) physical model, referred to as MoDL-QSM.  ...  Quantitative susceptibility mapping (QSM) has demonstrated great potential in quantifying tissue susceptibility in various brain diseases.  ...  For model-based deep learning, the network is embedded into the physical model to learn a regularization term.  ... 
doi:10.1016/j.neuroimage.2021.118376 pmid:34246768 fatcat:zf7gfneii5dejf7linnrlvwjla

Instant tissue field and magnetic susceptibility mapping from MR raw phase using Laplacian enabled deep neural networks [article]

Yang Gao, Zhuang Xiong, Amir Fazlollahi, Peter J Nestor, Viktor Vegh, Fatima Nasrallah, Craig Winter, G. Bruce Pike, Stuart Crozier, Feng Liu, Hongfu Sun
2022 arXiv   pre-print
This study develops a large-stencil Laplacian preprocessed deep learning-based neural network for near instant quantitative field and susceptibility mapping (i.e., iQFM and iQSM) from raw MR phase data  ...  Quantitative susceptibility mapping (QSM) is a valuable MRI post-processing technique that quantifies the magnetic susceptibility of body tissue from phase data.  ...  ACKNOWLEDGMENTS The authors would like to thank Dr Markus Barth for his helpful discussion.  ... 
arXiv:2111.07665v3 fatcat:ral2hjz2qfhxlkgceoe5qpe7lq

Learn Less, Infer More: Learning in the Fourier Domain for Quantitative Susceptibility Mapping

Junjie He, Lihui Wang, Ying Cao, Rongpin Wang, Yuemin Zhu
2022
Quantitative susceptibility mapping (QSM) aims to evaluate the distribution of magnetic susceptibility from magnetic resonance phase measurements by solving the ill-conditioned dipole inversion problem  ...  Its generalization ability and great sensitivity to susceptibility changes can make it a potential method for distinguishing some diseases.  ...  Feng et al. (2021) proposed an STI-based deep learning architecture for single-orientation QSM, referred to as MoDL-QSM, which can preserve the nature of anisotropic magnetic susceptibility in brain white  ... 
doi:10.3389/fnins.2022.837721 pmid:35250469 pmcid:PMC8888664 fatcat:lu5v6qrzordldlnoy2ydzquvfq