Author:
Wu Qing,Li Yuwei,Xu Lan,Feng Ruiming,Wei Hongjiang,Yang Qing,Yu Boliang,Liu Xiaozhao,Yu Jingyi,Zhang Yuyao
Publisher
Springer International Publishing
Reference24 articles.
1. Chen, Y., Christodoulou, A.G., Zhou, Z., Shi, F., Xie, Y., Li, D.: MRI super-resolution with GAN and 3d multi-level DenseNet: smaller, faster, and better. arXiv preprint arXiv:2003.01217 (2020)
2. Chen, Y., Shi, F., Christodoulou, A., Zhou, Z., Xie, Y., Li, D.: Efficient and Accurate MRI Super-Resolution Using a Generative Adversarial Network and 3D Multi-level Densely Connected Network, pp. 91–99, September 2018. https://doi.org/10.1007/978-3-030-00928-1_11
3. Delannoy, Q., et al.: SegSRGAN: super-resolution and segmentation using generative adversarial networks-application to neonatal brain MRI. Comput. Biol. Med. 120, 103755 (2020)
4. Ebner, M., et al.: An automated framework for localization, segmentation and super-resolution reconstruction of fetal brain MRI. NeuroImage 206, 116324 (2019). https://doi.org/10.1016/j.neuroimage.2019.116324
5. Gholipour, A., Estroff, J., Warfield, S.: Robust super-resolution volume reconstruction from slice acquisitions: application to fetal brain MRI. IEEE Trans. Med. Imag. 29, 1739–58 (2010). https://doi.org/10.1109/TMI.2010.2051680
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