A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density Noisier2Noise

20 May 2022

Papers citing "A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density Noisier2Noise"

5 / 5 papers shown

Title
Benchmarking Self-Supervised Learning Methods for Accelerated MRI Reconstruction Andrew Wang Steven McDonagh Mike Davies OOD SSL 106 0 0 19 Feb 2025
Ambient Diffusion Posterior Sampling: Solving Inverse Problems with Diffusion Models Trained on Corrupted Data Asad Aali Giannis Daras Brett Levac Sidharth Kumar Alexandros G. Dimakis Jonathan I. Tamir MedIm 56 9 0 13 Mar 2024
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient Descent over K-space Subsets Frédéric Wang Han Qi A. D. Goyeneche Reinhard Heckel Michael Lustig Efrat Shimron 19 4 0 05 Aug 2023
Ambient Diffusion: Learning Clean Distributions from Corrupted Data Giannis Daras Kulin Shah Y. Dagan Aravind Gollakota A. Dimakis Adam R. Klivans DiffM 37 64 0 30 May 2023
Self-Supervised Learning for MRI Reconstruction with a Parallel Network Training Framework Chenwenbao Hu Cheng Li Haifeng Wang Qiegen Liu Hairong Zheng Shanshan Wang OOD 84 45 0 26 Sep 2021