| Multi‐mask self‐supervised learning for physics‐guided neural networks in highly accelerated magnetic resonance imaging B Yaman, H Gu, SAH Hosseini, OB Demirel, S Moeller, J Ellermann, ... NMR in Biomedicine 35 (12), e4798, 2022 | 35 | 2022 |
| Revisiting -wavelet compressed-sensing MRI in the era of deep learning H Gu, B Yaman, S Moeller, J Ellermann, K Ugurbil, M Akçakaya Proceedings of the National Academy of Sciences 119 (33), e2201062119, 2022 | 18 | 2022 |
| Compressed Sensing MRI with ℓ1-Wavelet Reconstruction Revisited Using Modern Data Science Tools H Gu, B Yaman, K Ugurbil, S Moeller, M Akçakaya 2021 43rd Annual International Conference of the IEEE Engineering in …, 2021 | 11 | 2021 |
| Compressed sensing MRI revisited: Optimizing l1-wavelet reconstruction with modern data science tools H Gu, B Yaman, K Ugurbil, S Moeller, M Akcakaya Proceedings of the ISMRM, 274, 2021 | 3 | 2021 |
| Non-Cartesian Self-Supervised Physics-Driven Deep Learning Reconstruction for Highly-Accelerated Multi-Echo Spiral fMRI H Gu, C Zhang, Z Yu, C Rettenmeier, VA Stenger, M Akçakaya 2024 IEEE International Symposium on Biomedical Imaging (ISBI), 1-5, 2024 | | 2024 |
| Accelerated MRI with Deep Linear Convolutional Transform Learning H Gu, B Yaman, S Moeller, IY Chun, M Akçakaya 2022 IEEE 13th Annual Information Technology, Electronics and Mobile …, 2022 | | 2022 |
| Ten-fold accelerated multi-echo spiral fMRI using self-supervised physics-driven DL reconstruction Z Yu, H Gu, C Zhang, C Rettenmeier, M Akcakaya, VA Stenger | | |
| Learning Deep Linear Convolutional Transforms For Accelerated MRI H Gu, B Yaman, S Moeller, IY Chun, M Akçakaya | | |
Mehmet AkcakayaAssociate Professor, University of Minnesota在 umn.edu 的电子邮件经过验证
