Knoll, Florian, Hammernik, Kerstin, Zhang, Chi, Moeller, Steen, Pock, Thomas, Sodickson, Daniel K., and Akcakaya, Mehmet. Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. Retrieved from https://par.nsf.gov/biblio/10147849. IEEE Signal Processing Magazine 37.1 Web. doi:10.1109/MSP.2019.2950640.

Knoll, Florian, Hammernik, Kerstin, Zhang, Chi, Moeller, Steen, Pock, Thomas, Sodickson, Daniel K., & Akcakaya, Mehmet. Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. IEEE Signal Processing Magazine, 37 (1). Retrieved from https://par.nsf.gov/biblio/10147849. https://doi.org/10.1109/MSP.2019.2950640

Knoll, Florian, Hammernik, Kerstin, Zhang, Chi, Moeller, Steen, Pock, Thomas, Sodickson, Daniel K., and Akcakaya, Mehmet. "Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues". IEEE Signal Processing Magazine 37 (1). Country unknown/Code not available. https://doi.org/10.1109/MSP.2019.2950640. https://par.nsf.gov/biblio/10147849.

@article{osti_10147849,
place = {Country unknown/Code not available}, title = {Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues}, url = {https://par.nsf.gov/biblio/10147849}, DOI = {10.1109/MSP.2019.2950640}, abstractNote = {}, journal = {IEEE Signal Processing Magazine}, volume = {37}, number = {1}, author = {Knoll, Florian and Hammernik, Kerstin and Zhang, Chi and Moeller, Steen and Pock, Thomas and Sodickson, Daniel K. and Akcakaya, Mehmet}, }