A review and experimental evaluation of deep learning methods for MRI reconstruction

17 September 2021

Papers citing "A review and experimental evaluation of deep learning methods for MRI reconstruction"

7 / 7 papers shown

Title
Deep End-to-end Adaptive k-Space Sampling, Reconstruction, and Registration for Dynamic MRI George Yiasemis J. Sonke Jonas Teuwen 63 0 0 27 Nov 2024
Tumor likelihood estimation on MRI prostate data by utilizing k-Space information Moritz Rempe Fabian Horst C. Seibold Boris A. Hadaschik Marc Schlimbach Jan Egger Kevin Kröninger Felix Breuer M. Blaimer Jens Kleesiek 29 1 0 04 Jun 2024
To be or not to be stable, that is the question: understanding neural networks for inverse problems David Evangelista J. Nagy E. Morotti E. L. Piccolomini 23 4 0 24 Nov 2022
MAC-ReconNet: A Multiple Acquisition Context based Convolutional Neural Network for MR Image Reconstruction using Dynamic Weight Prediction Sriprabha Ramanarayanan Balamurali Murugesan Keerthi Ram M. Sivaprakasam 16 8 0 09 Nov 2021
eRAKI: Fast Robust Artificial neural networks for K-space Interpolation (RAKI) with Coil Combination and Joint Reconstruction Heng Yu Zijing Dong Y. Arefeen C. Liao K. Setsompop B. Bilgiç 24 3 0 07 Jul 2021
Zero-Shot Self-Supervised Learning for MRI Reconstruction Burhaneddin Yaman S. A. Hosseini Mehmet Akçakaya 16 65 0 15 Feb 2021
Regularization-Agnostic Compressed Sensing MRI Reconstruction with Hypernetworks Alan Q. Wang Adrian V. Dalca M. Sabuncu OOD 26 12 0 06 Jan 2021