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Multi-Scale Learned Iterative Reconstruction
v1v2v3 (latest)

Multi-Scale Learned Iterative Reconstruction

IEEE Transactions on Computational Imaging (TCI), 2019
1 August 2019
A. Hauptmann
J. Adler
Simon Arridge
Ozan Oktem
ArXiv (abs)PDFHTML

Papers citing "Multi-Scale Learned Iterative Reconstruction"

19 / 19 papers shown
Learning Regularization Functionals for Inverse Problems: A Comparative Study
Learning Regularization Functionals for Inverse Problems: A Comparative Study
J. Hertrich
Matthias Joachim Ehrhardt
Alexander Denker
Stanislas Ducotterd
Zhenghan Fang
...
German Shâma Wache
Martin Zach
Yasi Zhang
Matthias Joachim Ehrhardt
Sebastian Neumayer
228
10
0
02 Oct 2025
Equivariant Multiscale Learned Invertible Reconstruction for Cone Beam
  CT
Equivariant Multiscale Learned Invertible Reconstruction for Cone Beam CT
N. Moriakov
Jan-Jakob Sonke
Jonas Teuwen
135
0
0
20 Jan 2024
Glimpse: Generalized Locality for Scalable and Robust CT
Glimpse: Generalized Locality for Scalable and Robust CTIEEE Transactions on Medical Imaging (IEEE TMI), 2024
AmirEhsan Khorashadizadeh
Valentin Debarnot
Tianlin Liu
Ivan Dokmanić
479
5
0
01 Jan 2024
Learned reconstruction methods for inverse problems: sample error
  estimates
Learned reconstruction methods for inverse problems: sample error estimates
Luca Ratti
266
1
0
21 Dec 2023
Model-corrected learned primal-dual models for fast limited-view
  photoacoustic tomography
Model-corrected learned primal-dual models for fast limited-view photoacoustic tomography
A. Hauptmann
Jenni Poimala
MedIm
183
7
0
04 Apr 2023
Retrospective Motion Correction in Gradient Echo MRI by Explicit Motion
  Estimation Using Deep CNNs
Retrospective Motion Correction in Gradient Echo MRI by Explicit Motion Estimation Using Deep CNNs
M. S. Feinler
B. Hahn
MedIm
143
7
0
30 Mar 2023
Learned Interferometric Imaging for the SPIDER Instrument
Learned Interferometric Imaging for the SPIDER InstrumentRAS Techniques and Instruments (RTI), 2023
Matthijs Mars
M. Betcke
Jason D. McEwen
179
4
0
24 Jan 2023
Enhanced artificial intelligence-based diagnosis using CBCT with
  internal denoising: Clinical validation for discrimination of fungal ball,
  sinusitis, and normal cases in the maxillary sinus
Enhanced artificial intelligence-based diagnosis using CBCT with internal denoising: Clinical validation for discrimination of fungal ball, sinusitis, and normal cases in the maxillary sinus
Kyungsu Kim
Chae Yeon Lim
J. Shin
M. Chung
Y. Jung
132
25
0
29 Nov 2022
Unsupervised denoising for sparse multi-spectral computed tomography
Unsupervised denoising for sparse multi-spectral computed tomography
S. Inkinen
Mikael A. K. Brix
M. Nieminen
Simon Arridge
A. Hauptmann
212
2
0
02 Nov 2022
Deep Learning for Material Decomposition in Photon-Counting CT
Deep Learning for Material Decomposition in Photon-Counting CT
Alma Eguizabal
Ozan Oktem
Mats U. Persson
252
9
0
05 Aug 2022
3D helical CT Reconstruction with a Memory Efficient Learned Primal-Dual
  Architecture
3D helical CT Reconstruction with a Memory Efficient Learned Primal-Dual ArchitectureIEEE Transactions on Computational Imaging (TCI), 2022
Jevgenija Rudzusika
Buda Bajić
Thomas Koehler
Ozan Oktem
MedIm
288
6
0
24 May 2022
Learned Cone-Beam CT Reconstruction Using Neural Ordinary Differential
  Equations
Learned Cone-Beam CT Reconstruction Using Neural Ordinary Differential Equations
Mareike Thies
Fabian Wagner
Mingxuan Gu
Lukas Folle
Lina Felsner
Andreas Maier
174
6
0
19 Jan 2022
Regularizing Instabilities in Image Reconstruction Arising from Learned
  Denoisers
Regularizing Instabilities in Image Reconstruction Arising from Learned Denoisers
Abinash Nayak
248
0
0
21 Aug 2021
Learning the optimal Tikhonov regularizer for inverse problems
Learning the optimal Tikhonov regularizer for inverse problemsNeural Information Processing Systems (NeurIPS), 2021
Giovanni S. Alberti
Ernesto De Vito
Matti Lassas
Luca Ratti
Matteo Santacesaria
259
42
0
11 Jun 2021
Graph Convolutional Networks for Model-Based Learning in Nonlinear
  Inverse Problems
Graph Convolutional Networks for Model-Based Learning in Nonlinear Inverse ProblemsIEEE Transactions on Computational Imaging (IEEE Trans. Comput. Imaging), 2021
William Herzberg
D. Rowe
A. Hauptmann
S. Hamilton
GNNMedImAI4CE
245
44
0
28 Mar 2021
Solving Inverse Problems With Deep Neural Networks -- Robustness
  Included?
Solving Inverse Problems With Deep Neural Networks -- Robustness Included?
Martin Genzel
Jan Macdonald
M. März
AAMLOOD
207
131
0
09 Nov 2020
Deep Learning in Photoacoustic Tomography: Current approaches and future
  directions
Deep Learning in Photoacoustic Tomography: Current approaches and future directionsJournal of Biomedical Optics (JBO), 2020
A. Hauptmann
B. Cox
259
150
0
16 Sep 2020
On Learned Operator Correction in Inverse Problems
On Learned Operator Correction in Inverse Problems
Sebastian Lunz
A. Hauptmann
T. Tarvainen
Carola-Bibiane Schönlieb
Simon Arridge
233
4
0
14 May 2020
Solving Traveltime Tomography with Deep Learning
Solving Traveltime Tomography with Deep LearningCommunications in Mathematics and Statistics (CMS), 2019
Yuwei Fan
Lexing Ying
334
15
0
25 Nov 2019
1
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