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Physics-Driven Deep Learning for Computational Magnetic Resonance
  Imaging

Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging

23 March 2022
Kerstin Hammernik
Thomas Kustner
Burhaneddin Yaman
Zhengnan Huang
Daniel Rueckert
Florian Knoll
Mehmet Akçakaya
    PINN
    MedIm
    AI4CE
ArXivPDFHTML

Papers citing "Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging"

10 / 10 papers shown
Title
Hybrid Learning: A Novel Combination of Self-Supervised and Supervised Learning for MRI Reconstruction without High-Quality Training Reference
Hybrid Learning: A Novel Combination of Self-Supervised and Supervised Learning for MRI Reconstruction without High-Quality Training Reference
Haoyang Pei
Ding Xia
Xiang Xu
William Moore
Yao Wang
Hersh Chandarana
Li Feng
24
0
0
09 May 2025
Deep learning of personalized priors from past MRI scans enables fast, quality-enhanced point-of-care MRI with low-cost systems
Deep learning of personalized priors from past MRI scans enables fast, quality-enhanced point-of-care MRI with low-cost systems
Tal Oved
Beatrice Lena
Chloé F. Najac
Sheng Shen
Matthew S. Rosen
Andrew Webb
Efrat Shimron
MedIm
24
0
0
05 May 2025
Efficient Noise Calculation in Deep Learning-based MRI Reconstructions
Efficient Noise Calculation in Deep Learning-based MRI Reconstructions
Onat Dalmaz
Arjun D Desai
Reinhard Heckel
Tolga Çukur
Akshay Chaudhari
B. Hargreaves
24
0
0
04 May 2025
Deep Learning Assisted Outer Volume Removal for Highly-Accelerated Real-Time Dynamic MRI
Deep Learning Assisted Outer Volume Removal for Highly-Accelerated Real-Time Dynamic MRI
Merve Gülle
Sebastian Weingärtner
Mehmet Akçakaya
44
0
0
01 May 2025
Lightweight Hypercomplex MRI Reconstruction: A Generalized Kronecker-Parameterized Approach
H. Zhang
Jiahao Huang
Yinzhe Wu
Congren Dai
Fanwen Wang
Zhenxuan Zhang
Guang Yang
58
0
0
13 Mar 2025
Continuous K-space Recovery Network with Image Guidance for Fast MRI Reconstruction
Yucong Meng
Zhiwei Yang
Minghong Duan
Yonghong Shi
Zhijian Song
36
1
0
18 Nov 2024
K-band: Self-supervised MRI Reconstruction via Stochastic Gradient
  Descent over K-space Subsets
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
Uncertainty Estimation and Out-of-Distribution Detection for Deep
  Learning-Based Image Reconstruction using the Local Lipschitz
Uncertainty Estimation and Out-of-Distribution Detection for Deep Learning-Based Image Reconstruction using the Local Lipschitz
D. Bhutto
Bo Zhu
J. Liu
Neha Koonjoo
H. Li
Bruce Rosen
M. Rosen
UQCV
OOD
15
2
0
12 May 2023
A theoretical framework for self-supervised MR image reconstruction
  using sub-sampling via variable density Noisier2Noise
A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density Noisier2Noise
Charles Millard
M. Chiew
32
32
0
20 May 2022
Zero-Shot Self-Supervised Learning for MRI Reconstruction
Zero-Shot Self-Supervised Learning for MRI Reconstruction
Burhaneddin Yaman
S. A. Hosseini
Mehmet Akçakaya
21
67
0
15 Feb 2021
1