Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms
- DOI
- 10.1109/jstsp.2020.3003170
- Published
- 2020-10
- Container
- IEEE Journal of Selected Topics in Signal Processing
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/jstsp.2020.3003170,
title = {Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms},
author = {Seyed Amir Hossein Hosseini and Burhaneddin Yaman and Steen Moeller and Mingyi Hong and Mehmet Akcakaya},
year = {2020},
journal = {IEEE Journal of Selected Topics in Signal Processing},
doi = {10.1109/jstsp.2020.3003170},
url = {https://doi.org/10.1109/jstsp.2020.3003170}
}RIS
TY - JOUR TI - Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms AU - Seyed Amir Hossein Hosseini AU - Burhaneddin Yaman AU - Steen Moeller AU - Mingyi Hong AU - Mehmet Akcakaya PY - 2020 JO - IEEE Journal of Selected Topics in Signal Processing DO - 10.1109/jstsp.2020.3003170 UR - https://doi.org/10.1109/jstsp.2020.3003170 ER -
APA
Hosseini, S. A. H., Yaman, B., Moeller, S., Hong, M., & Akcakaya, M. (2020). Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms. IEEE Journal of Selected Topics in Signal Processing. https://doi.org/10.1109/jstsp.2020.3003170
Source records
- crossref · retrieved 2026-11-10T11:07:50.844Z