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README.md

DIMENSION:Dynamic MR Imaging with Both K-space and Spatial Prior via Multi-Supervised Network Training
- Requirements
- Acknowledge

DIMENSION:Dynamic MR Imaging with Both K-space and Spatial Prior via Multi-Supervised Network Training

This repository provides a tensorflow implementation used in our publications

Shanshan Wang#, Ziwen Ke#, Huitao Cheng, Sen Jia, Leslie Ying, Hairong Zheng, Dong Liang. DIMENSION: Dynamic MR Imaging with Both K-space and Spatial Prior Knowledge Obtained via Multi-Supervised Network Training, NMR in Biomedicine, DOI: 10.1002/nbm.4131, 2019

If you use this code, please refer to:

@article{doi: 10.1002/nbm.4131,
    author = {Shanshan Wang, Ziwen Ke, Huitao Cheng, Sen Jia, Leslie Ying, Hairong Zheng, Dong Liang},
    title = {DIMENSION: Dynamic MR Imaging with Both K-space and Spatial Prior Knowledge Obtained via Multi-Supervised Network Training},
    journal = {NMR in Biomedicine},
    doi = {10.1002/nbm.4131, 2019},
}

Requirements

This framework requires Python 2.7 and the tensorflow repository, the main dependencies are as follows:

TensorFlow 1.3
python 2.7
scipy 1.2.1
h5py 2.9.0
scikit-image 0.15.0

Acknowledge

Some of the auxiliary code are provided by Jo Schlemper, for example "utils".

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Python

README.md

DIMENSION:Dynamic MR Imaging with Both K-space and Spatial Prior via Multi-Supervised Network Training

Requirements

Acknowledge

Contributors (1) All

Contributors (1)
All