Physics-Driven Deep Learning for Computational Magnetic Resonance
Imaging

Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging

23 March 2022

Kerstin Hammernik

Burhaneddin Yaman

Daniel Rueckert

Mehmet Akçakaya

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

12 / 12 papers shown

Title
Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems Jeffrey Wen Rizwan Ahmad Philip Schniter 29 0 0 14 May 2025
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 34 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 Tal Oved Beatrice Lena Chloé F. Najac Sheng Shen Matthew S. Rosen Andrew Webb Efrat Shimron MedIm 36 0 0 05 May 2025
Efficient Noise Calculation in Deep Learning-based MRI Reconstructions Onat Dalmaz Arjun D Desai Reinhard Heckel Tolga Çukur Akshay Chaudhari B. Hargreaves 29 0 0 04 May 2025
Deep Learning Assisted Outer Volume Removal for Highly-Accelerated Real-Time Dynamic MRI Merve Gülle Sebastian Weingärtner Mehmet Akçakaya 46 0 0 01 May 2025
Lightweight Hypercomplex MRI Reconstruction: A Generalized Kronecker-Parameterized Approach Haiqi Zhang Jiahao Huang Yinzhe Wu Congren Dai Fanwen Wang Zhenxuan Zhang Guang Yang 63 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 44 1 0 18 Nov 2024
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction Jeffrey Wen Rizwan Ahmad Philip Schniter 39 2 0 28 May 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 33 5 0 05 Aug 2023
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 Charles Millard M. Chiew 40 33 0 20 May 2022
Zero-Shot Self-Supervised Learning for MRI Reconstruction Burhaneddin Yaman S. A. Hosseini Mehmet Akçakaya 21 67 0 15 Feb 2021