Motion Compensated Unsupervised Deep Learning for 5D MRI
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Publisher
Springer Nature Switzerland
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-43999-5_40
Reference15 articles.
1. Bustin, A., Fuin, N., Botnar, R.M., Prieto, C.: From compressed-sensing to artificial intelligence-based cardiac MRI reconstruction. Front. Cardiovasc. Med. 7, 17 (2020). https://doi.org/10.3389/FCVM.2020.00017/BIBTEX
2. Feng, L., Axel, L., Chandarana, H., Block, K.T., Sodickson, D.K., Otazo, R.: XD-grasp: golden-angle radial MRI with reconstruction of extra motion-state dimensions using compressed sensing. Magn. Reson. Med. 75(2), 775–788 (2016)
3. Feng, L., et al.: 5D whole-heart sparse MRI. Magn. Reson. Med. 79(2), 826–838 (2017). https://doi.org/10.1002/mrm.26745
4. Kim, D., Cauley, S.F., Nayak, K.S., Leahy, R.M., Haldar, J.P.: Region-optimized virtual (ROVir) coils: localization and/or suppression of spatial regions using sensor-domain beamforming. Magn. Reson. Med. 86(1), 197–212 (2021). https://doi.org/10.1002/mrm.28706
5. Mohsin, Y.Q., Poddar, S., Jacob, M.: Free-breathing & ungated cardiac MRI using iterative SToRM (i-SToRM). IEEE Trans. Med. Imaging 38(10), 2303–2313 (2019). https://doi.org/10.1109/tmi.2019.2908140
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