Sampling possible reconstructions of undersampled acquisitions in MR imaging with a deep learned prior

KC Tezcan, N Karani, CF Baumgartner… - … on Medical Imaging, 2022 - ieeexplore.ieee.org
Undersampling the k-space during MR acquisitions saves time, however results in an ill-
posed inversion problem, leading to an infinite set of images as possible solutions …
被引用次数：11 相关文章

Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep Learned Prior

KC Tezcan, N Karani… - IEEE Transactions …, 2022 - research-collection.ethz.ch
Undersampling the k-space during MR acquisitions saves time, however results in an ill-
posed inversion problem, leading to an infinite set of images as possible solutions …

Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep Learned Prior

KC Tezcan, N Karani… - IEEE transactions …, 2022 - pubmed.ncbi.nlm.nih.gov
Undersampling the k-space during MR acquisitions saves time, however results in an ill-
posed inversion problem, leading to an infinite set of images as possible solutions …

[引用][C] Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep Learned Prior

KC Tezcan, N Karani… - IEEE Transactions …, 2022 - tobias-lib.ub.uni-tuebingen.de
Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep
Learned Prior Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging …

[引用][C] Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep Learned Prior

KC Tezcan, N Karani… - … on Medical Imaging, 2022 - ub01.uni-tuebingen.de
Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep
Learned Prior Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging …

Sampling Possible Reconstructions of Undersampled Acquisitions in MR Imaging With a Deep Learned Prior.

KC Tezcan, N Karani, CF Baumgartner… - IEEE Transactions on …, 2022 - europepmc.org
Undersampling the k-space during MR acquisitions saves time, however results in an ill-
posed inversion problem, leading to an infinite set of images as possible solutions …