Mehmet Akcakaya, Ph.D.
Affiliations: | 2010 | Harvard University, Cambridge, MA, United States |
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"Mehmet Akcakaya"Parents
Sign in to add mentor| Vahid Tarokh | grad student | 2010 | Harvard | |
| (An information theoretic approach to compressed sensing and its utility in magnetic resonance imaging.) | ||||
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Publications
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| Demirel OB, Zhang C, Yaman B, et al. (2023) High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI. Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual International Conference. 2023: 1-4 |
| Demirel ÖB, Weingärtner S, Moeller S, et al. (2023) Improved Simultaneous Multi-slice imaging with Composition of k-space Interpolations (SMS-COOKIE) for myocardial T1 mapping. Plos One. 18: e0283972 |
| Demirel ÖB, Zhang C, Yaman B, et al. (2023) High-fidelity Database-free Deep Learning Reconstruction for Real-time Cine Cardiac MRI. Biorxiv : the Preprint Server For Biology |
| Weingärtner S, Demirel ÖB, Gama F, et al. (2022) Cardiac phase-resolved late gadolinium enhancement imaging. Frontiers in Cardiovascular Medicine. 9: 917180 |
| Demirel OB, Yaman B, Moeller S, et al. (2022) Signal-Intensity Informed Multi-Coil MRI Encoding Operator for Improved Physics-Guided Deep Learning Reconstruction of Dynamic Contrast-Enhanced MRI. Annual International Conference of the Ieee Engineering in Medicine and Biology Society. Ieee Engineering in Medicine and Biology Society. Annual International Conference. 2022: 1472-1476 |
| Gu H, Yaman B, Moeller S, et al. (2022) Revisiting [Formula: see text]-wavelet compressed-sensing MRI in the era of deep learning. Proceedings of the National Academy of Sciences of the United States of America. 119: e2201062119 |
| Zhang C, Moeller S, Demirel OB, et al. (2022) Residual RAKI: A Hybrid Linear and Non-Linear Approach for Scan-Specific k-space Deep Learning. Neuroimage. 119248 |
| Knoll F, Hammernik K, Zhang C, et al. (2020) Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. Ieee Signal Processing Magazine. 37: 128-140 |
| Hosseini SAH, Yaman B, Moeller S, et al. (2020) Dense Recurrent Neural Networks for Accelerated MRI: History-Cognizant Unrolling of Optimization Algorithms. Ieee Journal of Selected Topics in Signal Processing. 14: 1280-1291 |
| Moeller S, Pisharady Kumar P, Andersson J, et al. (2020) Diffusion Imaging in the Post-HCPEra. Journal of Magnetic Resonance Imaging : Jmri |