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Found 2 papers, 1 papers with code
DeepSTI: Towards Tensor Reconstruction using Fewer Orientations in Susceptibility Tensor Imaging
Experimental results using both simulation and in vivo human data demonstrate great improvement over state-of-the-art algorithms in terms of the reconstructed tensor image, principal eigenvector maps and tractography results, while allowing for tensor reconstruction with MR phase measured at much less than six different orientations.
Learned Proximal Networks for Quantitative Susceptibility Mapping
More importantly, this framework is believed to be the first deep learning QSM approach that can naturally handle an arbitrary number of phase input measurements without the need for any ad-hoc rotation or re-training.
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