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Bayesian Uncertainty Estimation of Learned Variational MRI
  Reconstruction

Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction

12 February 2021
Dominik Narnhofer
Alexander Effland
Erich Kobler
Kerstin Hammernik
Florian Knoll
T. Pock
    UQCV
    BDL
ArXivPDFHTML

Papers citing "Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction"

23 / 23 papers shown
Title
Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems
Conformal Bounds on Full-Reference Image Quality for Imaging Inverse Problems
Jeffrey Wen
Rizwan Ahmad
Philip Schniter
29
0
0
14 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
29
0
0
04 May 2025
Uncertainty Estimation for Trust Attribution to Speed-of-Sound Reconstruction with Variational Networks
Uncertainty Estimation for Trust Attribution to Speed-of-Sound Reconstruction with Variational Networks
Sonia Laguna
Lin Zhang
Can Deniz Bezek
Monika Farkas
Dieter Schweizer
Rahel A. Kubik-Huch
O. Goksel
OOD
35
0
0
15 Apr 2025
BUFF: Bayesian Uncertainty Guided Diffusion Probabilistic Model for Single Image Super-Resolution
BUFF: Bayesian Uncertainty Guided Diffusion Probabilistic Model for Single Image Super-Resolution
Zihao He
Shengchuan Zhang
R. Hu
Yunhang Shen
Yuyao Zhang
DiffM
57
0
0
04 Apr 2025
How Should We Evaluate Uncertainty in Accelerated MRI Reconstruction?
Luca Trautmann
Peter Wijeratne
Itamar Ronen
Ivor Simpson
61
0
0
13 Mar 2025
Guiding Quantitative MRI Reconstruction with Phase-wise Uncertainty
Guiding Quantitative MRI Reconstruction with Phase-wise Uncertainty
Haozhong Sun
Zhongsen Li
Chenlin Du
Haokun Li
Yajie Wang
Huijun Chen
59
0
0
28 Feb 2025
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal
  Prediction
Task-Driven Uncertainty Quantification in Inverse Problems via Conformal Prediction
Jeffrey Wen
Rizwan Ahmad
Philip Schniter
39
2
0
28 May 2024
NPB-REC: A Non-parametric Bayesian Deep-learning Approach for
  Undersampled MRI Reconstruction with Uncertainty Estimation
NPB-REC: A Non-parametric Bayesian Deep-learning Approach for Undersampled MRI Reconstruction with Uncertainty Estimation
Samah Khawaled
Moti Freiman
UQCV
37
3
0
06 Apr 2024
R2D2 image reconstruction with model uncertainty quantification in radio
  astronomy
R2D2 image reconstruction with model uncertainty quantification in radio astronomy
Amir Aghabiglou
Chung San Chu
A. Dabbech
Yves Wiaux
31
0
0
26 Mar 2024
A review of uncertainty quantification in medical image analysis:
  probabilistic and non-probabilistic methods
A review of uncertainty quantification in medical image analysis: probabilistic and non-probabilistic methods
Ling Huang
S. Ruan
Yucheng Xing
Mengling Feng
41
20
0
09 Oct 2023
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines
Propagation and Attribution of Uncertainty in Medical Imaging Pipelines
Leonhard F. Feiner
M. Menten
Kerstin Hammernik
Paul Hager
Wenqi Huang
Rafael Azevedo
R. Braren
Georgios Kaissis
MedIm
11
3
0
28 Sep 2023
Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction
Uncertainty Estimation and Propagation in Accelerated MRI Reconstruction
Paul Fischer
Thomas Kustner
Christian F. Baumgartner
29
8
0
04 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
PixCUE: Joint Uncertainty Estimation and Image Reconstruction in MRI
  using Deep Pixel Classification
PixCUE: Joint Uncertainty Estimation and Image Reconstruction in MRI using Deep Pixel Classification
Mevan Ekanayake
Kamlesh Pawar
Gary Egan
Zhaolin Chen
UQCV
18
0
0
28 Feb 2023
A Review of Uncertainty Estimation and its Application in Medical
  Imaging
A Review of Uncertainty Estimation and its Application in Medical Imaging
K. Zou
Zhihao Chen
Xuedong Yuan
Xiaojing Shen
Meng Wang
Huazhu Fu
UQCV
46
86
0
16 Feb 2023
Posterior-Variance-Based Error Quantification for Inverse Problems in
  Imaging
Posterior-Variance-Based Error Quantification for Inverse Problems in Imaging
Dominik Narnhofer
Andreas Habring
M. Holler
T. Pock
25
14
0
23 Dec 2022
Physics-Driven Deep Learning for Computational Magnetic Resonance
  Imaging
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging
Kerstin Hammernik
Thomas Kustner
Burhaneddin Yaman
Zhengnan Huang
Daniel Rueckert
Florian Knoll
Mehmet Akçakaya
PINN
MedIm
AI4CE
24
69
0
23 Mar 2022
Bayesian MRI Reconstruction with Joint Uncertainty Estimation using
  Diffusion Models
Bayesian MRI Reconstruction with Joint Uncertainty Estimation using Diffusion Models
Guanxiong Luo
Moritz Blumenthal
Martin Heide
M. Uecker
DiffM
MedIm
16
69
0
03 Feb 2022
Posterior temperature optimized Bayesian models for inverse problems in
  medical imaging
Posterior temperature optimized Bayesian models for inverse problems in medical imaging
M. Laves
Malte Tolle
Alexander Schlaefer
Sandy Engelhardt
35
10
0
02 Feb 2022
SoftDropConnect (SDC) -- Effective and Efficient Quantification of the
  Network Uncertainty in Deep MR Image Analysis
SoftDropConnect (SDC) -- Effective and Efficient Quantification of the Network Uncertainty in Deep MR Image Analysis
Qing Lyu
C. Whitlow
Ge Wang
UQCV
BDL
15
1
0
20 Jan 2022
A review and experimental evaluation of deep learning methods for MRI
  reconstruction
A review and experimental evaluation of deep learning methods for MRI reconstruction
Arghya Pal
Yogesh Rathi
3DV
47
41
0
17 Sep 2021
Progressively Volumetrized Deep Generative Models for Data-Efficient
  Contextual Learning of MR Image Recovery
Progressively Volumetrized Deep Generative Models for Data-Efficient Contextual Learning of MR Image Recovery
Mahmut Yurt
Muzaffer Özbey
S. Dar
Berk Tınaz
K. Oguz
Tolga Çukur
MedIm
33
29
0
27 Nov 2020
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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