Fetching the paper…
Reading the bibliography…
In the last years, the design of image reconstruction methods in the field of quantitative Magnetic Resonance Imaging (qMRI) has experienced a paradigm shift.
Nuclear induction
Felix Bloch · 1946
Earlier work this paper cites.
An algorithm for least-squares estimation of nonlinear parameters
Donald W Marquardt · 1963
Earlier work this paper cites.
Tumor detection by nuclear magnetic resonance
Raymond Damadian · 1971
Earlier work this paper cites.
Image formation by induced local interactions: examples employing nuclear magnetic resonance
Paul C. Lauterbur · 1973
Earlier work this paper cites.
Sur l’approximation, par éléments finis d’ordre un, et la résolution, par pénalisation-dualité d’une classe de problèmes de dirichlet non linéaires
Roland Glowinski and Americo Marroco · 1975
Earlier work this paper cites.
A dual algorithm for the solution of nonlinear variational problems via finite element approximation
Daniel Gabay and Bertrand Mercier · 1976
Earlier work this paper cites.
Multilayer feedforward networks are universal approximators
Kurt Hornik, Maxwell Stinchcombe, and Halbert White · 1989
Earlier work this paper cites.
On the limited memory BFGS method for large scale optimization
Dong C Liu and Jorge Nocedal · 1989
Earlier work this paper cites.
Fast spiral coronary artery imaging
Craig H. Meyer, Bob S. Hu, Dwight G. Nishimura, and Albert Macovski · 1992
Earlier work this paper cites.
Nonlinear total variation based noise removal algorithms
Leonid I. Rudin, Stanley Osher, and Emad Fatemi · 1992
Earlier work this paper cites.
Orthogonal matching pursuit: Recursive function approximation with applications to wavelet decomposition
Yagyensh Chandra Pati, Ramin Rezaiifar, and Perinkulam Sambamurthy Krishnaprasad · 1993
Earlier work this paper cites.
Ideal spatial adaptation by wavelet shrinkage
David L. Donoho and Iain M. Johnstone · 1994
Earlier work this paper cites.
Training with noise is equivalent to Tikhonov regularization
Chris M. Bishop · 1995
Earlier work this paper cites.
Regularization of inverse problems
Heinz Werner Engl, Martin Hanke, and Andreas Neubauer · 1996
Earlier work this paper cites.
Image recovery via total variation minimization and related problems
Antonin Chambolle and Pierre-Louis Lions · 1997
Earlier work this paper cites.
A regularizing Levenberg-Marquardt scheme, with applications to inverse groundwater filtration problems
Martin Hanke · 1997
Earlier work this paper cites.
Magnetic resonance imaging
G.A. Wright · 1997
Earlier work this paper cites.
Numerical optimization
Jorge Nocedal and Stephen J Wright · 1999
Earlier work this paper cites.
Approximation theory of the MLP model in neural networks
Allan Pinkus · 1999
Earlier work this paper cites.
Adaptive wavelet thresholding for image denoising and compression
S. G. Chang, B. Yu, and M. Vetterli · 2000
Earlier work this paper cites.
Structural properties of solutions to total variation regularization problems
Wolfgang Ring · 2000
Earlier work this paper cites.
Advances in sensitivity encoding with arbitrary k-space trajectories
Klaas P. Pruessmann, Markus Weiger, Peter Börnert, and Peter Boesiger · 2001
Earlier work this paper cites.
k-t BLAST and k-t SENSE: dynamic MRI with high frame rate exploiting spatiotemporal correlations
Jeffrey Tsao, Peter Boesiger, and Klaas P Pruessmann · 2003
Earlier work this paper cites.
The general inefficiency of batch training for gradient descent learning
D. Randall Wilson and Tony R. Martinez · 2003
Earlier work this paper cites.
Tomographic image reconstruction using artificial neural networks
P. Paschalis, N. D. Giokaris, A. Karabarbounis, G. K. Loudos, D. Maintas, C. N. Papanicolas, V. Spanoudaki, Ch Tsoumpas, and E. Stiliaris · 2004
Earlier work this paper cites.
Image quality assessment: from error visibility to structural similarity
Zhou Wang, Alan C. Bovik, Hamid R. Sheikh, and Eero P. Simoncelli · 2004
Earlier work this paper cites.
Fields of experts: A framework for learning image priors
Stefan Roth and Michael J. Black · 2005
Earlier work this paper cites.
K-SVD: An algorithm for designing overcomplete dictionaries for sparse representation
Michal Aharon, Michael Elad, and Alfred Bruckstein · 2006
Earlier work this paper cites.
Twenty new digital brain phantoms for creation of validation image data bases
Berengère Aubert-Broche, Mark Griffin, G. Bruce Pike, Alan C. Evans, and D. Louis Collins · 2006
Earlier work this paper cites.
Undersampled radial MRI with multiple coils. Iterative image reconstruction using a total variation constraint
Kai Tobias Block, Martin Uecker, and Jens Frahm · 2007
Earlier work this paper cites.
Sparse MRI: The application of compressed sensing for rapid MR imaging
Michael Lustig, David Donoho, and John M. Pauly · 2007
Earlier work this paper cites.
Fast joint reconstruction of dynamic R2* and field maps in functional MRI
Valur T. Olafsson, Douglas C. Noll, and Jeffrey A. Fessler · 2008
Earlier work this paper cites.
Image reconstruction by regularized nonlinear inversion–joint estimation of coil sensitivities and image content
Martin Uecker, Thorsten Hohage, Kai Tobias Block, and Jens Frahm · 2008
Earlier work this paper cites.
Model-based iterative reconstruction for radial fast spin-echo MRI
Kai Tobias Block, Martin Uecker, and Jens Frahm · 2009
Earlier work this paper cites.
k-t PCA: temporally constrained k-t BLAST reconstruction using principal component analysis
Henrik Pedersen, Sebastian Kozerke, Steffen Ringgaard, Kay Nehrke, and Won Yong Kim · 2009
Earlier work this paper cites.
Variational methods in imaging
Otmar Scherzer, Markus Grasmair, Harald Grossauer, Markus Haltmeier, and Frank Lenzen · 2009
Earlier work this paper cites.
Total generalized variation
Kristian Bredies, Karl Kunisch, and Thomas Pock · 2010
Earlier work this paper cites.
Compressed sensing reconstruction for magnetic resonance parameter mapping
Mariya Doneva, Peter Börnert, Holger Eggers, Christian Stehning, Julien Sénégas, and Alfred Mertins · 2010
Earlier work this paper cites.
Learning fast approximations of sparse coding
Karol Gregor and Yann LeCun · 2010
Earlier work this paper cites.
MR image reconstruction from highly undersampled k-space data by dictionary learning
Saiprasad Ravishankar and Yoram Bresler · 2010
Earlier work this paper cites.
Dictionaries for sparse representation modeling
Ron Rubinstein, Alfred M. Bruckstein, and Michael Elad · 2010
Earlier work this paper cites.
Distributed optimization and statistical learning via the alternating direction method of multipliers
Stephen Boyd, Neal Parikh, Eric Chu, Borja Peleato, and Jonathan Eckstein · 2011
Earlier work this paper cites.
A first-order primal-dual algorithm for convex problems with applications to imaging
Antonin Chambolle and Thomas Pock · 2011
Earlier work this paper cites.
Second order total generalized variation (TGV) for MRI
Florian Knoll, Kristian Bredies, Thomas Pock, and Rudolf Stollberger · 2011
Earlier work this paper cites.
Natural image denoising: Optimality and inherent bounds
Anat Levin and Boaz Nadler · 2011
Earlier work this paper cites.
Fast MR parameter mapping using k-t principal component analysis
Frederike H. Petzschner, Irene P. Ponce, Martin Blaimer, Peter M. Jakob, and Felix A. Breuer · 2011
Earlier work this paper cites.
Tomographic image reconstruction based on artificial neural network (ANN) techniques
Maria Argyrou, Dimitris Maintas, Charalampos Tsoumpas, and Efstathios Stiliaris · 2012
Earlier work this paper cites.
Compressive sensing MRI with wavelet tree sparsity
Chen Chen and Junzhou Huang · 2012
Earlier work this paper cites.
Neural networks for machine learning lecture 6a overview of mini-batch gradient descent
Geoffrey Hinton, Nitish Srivastava, and Kevin Swersky · 2012
Earlier work this paper cites.
T2 mapping from highly undersampled data by reconstruction of principal component coefficient maps using compressed sensing
Chuan Huang, Christian G Graff, Eric W Clarkson, Ali Bilgin, and Maria I Altbach · 2012
Earlier work this paper cites.
Adadelta: an adaptive learning rate method
Matthew D Zeiler · 2012
Earlier work this paper cites.
A Guide to the TV Zoo
Martin Burger and Stanley Osher · 2013
Earlier work this paper cites.
Magnetic resonance fingerprinting
Dan Ma, Vikas Gulani, Nicole Seiberlich, Kecheng Liu, Jeffrey L. Sunshine, Jeffrey L. Duerk, and Mark A. Griswold · 2013
Earlier work this paper cites.
Plug-and-play priors for model based reconstruction
Singanallur V Venkatakrishnan, Charles A Bouman, and Brendt Wohlberg · 2013
Earlier work this paper cites.
Compressed sensing dynamic cardiac cine MRI using learned spatiotemporal dictionary
Yanhua Wang and Leslie Ying · 2013
Earlier work this paper cites.
Dictionary learning and time sparsity for dynamic MR data reconstruction
Jose Caballero, Anthony N. Price, Daniel Rueckert, and Joseph V. Hajnal · 2014
Earlier work this paper cites.
A compressed sensing framework for magnetic resonance fingerprinting
Mike Davies, Gilles Puy, Pierre Vandergheynst, and Yves Wiaux · 2014
Earlier work this paper cites.
Functional-analytic and numerical issues in splitting methods for total variation-based image reconstruction
Micahel Hintermüller, Carlos N Rautenberg, and Jooyoung Hahn · 2014
Earlier work this paper cites.
Khalid Jalalzai · 2014
Earlier work this paper cites.
SVD compression for magnetic resonance fingerprinting in the time domain
Debra F. McGivney, Eric Pierre, Dan Ma, Yun Jiang, Haris Saybasili, Vikas Gulani, and Mark A. Griswold · 2014
Earlier work this paper cites.
Sparse modeling: theory, algorithms, and applications
Irina Rish and Genady Grabarnik · 2014
Earlier work this paper cites.
Separable cosparse analysis operator learning
Matthias Seibert, Julian Wörmann, Rémi Gribonval, and Martin Kleinsteuber · 2014
Earlier work this paper cites.
Reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning
Ying Song, Zhen Zhu, Yang Lu, Qiegen Liu, and Jun Zhao · 2014
Earlier work this paper cites.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian J Goodfellow, and Rob Fergus · 2014
Earlier work this paper cites.
ESPIRiT–an eigenvalue approach to autocalibrating parallel MRI: where SENSE meets GRAPPA
Martin Uecker, Peng Lai, Mark J. Murphy, Patrick Virtue, Michael Elad, John M. Pauly, Shreyas S. Vasanawala, and Michael Lustig · 2014
Earlier work this paper cites.
Total Variation in Imaging
Vincent Caselles, Antonin Chambolle, and Matteo Novaga · 2015
Earlier work this paper cites.
Some remarks on the staircasing phenomenon in total variation-based image denoising
K. Jalalzai · 2015
Earlier work this paper cites.
A review of optimization and quantification techniques for chemical exchange saturation transfer MRI toward sensitive in vivo imaging
Jinsuh Kim, Yin Wu, Yingkun Guo, Hairong Zheng, and Phillip Zhe Sun · 2015
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba · 2015
Earlier work this paper cites.
Efficient blind compressed sensing using sparsifying transforms with convergence guarantees and application to magnetic resonance imaging
Saiprasad Ravishankar and Yoram Bresler · 2015
Cited alongside, same era.
U-net: Convolutional networks for biomedical image segmentation
Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015
Cited alongside, same era.
Efficient algorithms for convolutional sparse representations
Brendt Wohlberg · 2015
Cited alongside, same era.
Infimal convolution regularisation functionals of BV and L p \mathrm{L}^{p} spaces. Part I: The finite p p case
Martin Burger, Kostas Papafitsoros, Evangelos Papoutsellis, and Carola-Bibiane Schönlieb · 2016
Cited alongside, same era.
An introduction to continuous optimization for imaging
Antonin Chambolle and Thomas Pock · 2016
Cited alongside, same era.
Deep learning
On instabilities of deep learning in image reconstruction and the potential costs of AI
Vegard Antun, Francesco Renna, Clarice Poon, Ben Adcock, and Anders C. Hansen · 2020
Later among the works it cites.
Untrained modified deep decoder for joint denoising parallel imaging reconstruction
Sukrit Arora, Volkert Roeloffs, and Michael Lustig · 2020
Later among the works it cites.
Compressive MR fingerprinting reconstruction with neural proximal gradient iterations
Dongdong Chen, Mike E Davies, and Mohammad Golbabaee · 2020
Later among the works it cites.
DeepCEST 3T: Robust MRI parameter determination and uncertainty quantification with neural networks—application to CEST imaging of the human brain at 3T
Felix Glang, Anagha Deshmane, Sergey Prokudin, Florian Martin, Kai Herz, Tobias Lindig, Benjamin Bender, Klaus Scheffler, and Moritz Zaiss · 2020
Later among the works it cites.
A myocardial T1-mapping framework with recurrent and U-Net convolutional neural networks
Haris Jeelani, Yang Yang, Ruixi Zhou, Christopher M Kramer, Michael Salerno, and Daniel S Weller · 2020
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Ian Goodfellow, Yoshua Bengio, and Aaron Courville · 2016
Cited alongside, same era.
Compressed sensing dynamic MRI reconstruction using GPU-accelerated 3D convolutional sparse coding
Tran Minh Quan and Won-Ki Jeong · 2016
Cited alongside, same era.
Compressed sensing reconstruction of dynamic contrast enhanced MRI using GPU-accelerated convolutional sparse coding
Tran Minh Quan and Won-Ki Jeong · 2016
Cited alongside, same era.
An overview of gradient descent optimization algorithms
Sebastian Ruder · 2016
Cited alongside, same era.
Deep ADMM-Net for compressive sensing MRI
Jian Sun, Huibin Li, Zongben Xu, et al · 2016
Cited alongside, same era.
Accelerating magnetic resonance imaging via deep learning
Shanshan Wang, Zhenghang Su, Leslie Ying, Xi Peng, Shun Zhu, Feng Liang, Dagan Feng, and Dong Liang · 2016
Cited alongside, same era.
Optnet: Differentiable optimization as a layer in neural networks
Brandon Amos and J Zico Kolter · 2017
Cited alongside, same era.
Later among the works it cites.
Reparameterizing convolutions for incremental multi-task learning without task interference
Menelaos Kanakis, David Bruggemann, Suman Saha, Stamatios Georgoulis, Anton Obukhov, and Luc Van Gool · 2020
Later among the works it cites.
Neural networks-based regularization for large-scale medical image reconstruction
Andreas Kofler, Markus Haltmeier, Tobias Schaeffter, Marc Kachelrieß, Marc Dewey, Christian Wald, and Christoph Kolbitsch · 2020
Later among the works it cites.
RARE: Image reconstruction using deep priors learned without groundtruth
Jiaming Liu, Yu Sun, Cihat Eldeniz, Weijie Gan, Hongyu An, and Ulugbek S Kamilov · 2020
Later among the works it cites.
Noisier2noise: Learning to denoise from unpaired noisy data
Nick Moran, Dan Schmidt, Yu Zhong, and Patrick Coady · 2020
Later among the works it cites.
Higher-order total directional variation: Imaging applications
Simone Parisotto, Jan Lellmann, Simon Masnou, and Carola-Bibiane Schönlieb · 2020
Later among the works it cites.
U2-Net: Going deeper with nested U-structure for salient object detection
Xuebin Qin, Zichen Zhang, Chenyang Huang, Masood Dehghan, Osmar R. Zaiane, and Martin Jagersand · 2020
Later among the works it cites.
Implicit neural representations with periodic activation functions
Vincent Sitzmann, Julien Martel, Alexander Bergman, David Lindell, and Gordon Wetzstein · 2020
Later among the works it cites.
End-to-end variational networks for accelerated MRI reconstruction
Anuroop Sriram, Jure Zbontar, Tullie Murrell, Aaron Defazio, C Lawrence Zitnick, Nafissa Yakubova, Florian Knoll, and Patricia Johnson · 2020
Later among the works it cites.
Self-supervised learning of physics-guided reconstruction neural networks without fully sampled reference data
Burhaneddin Yaman, Seyed Amir Hossein Hosseini, Steen Moeller, Jutta Ellermann, Kâmil Uğurbil, and Mehmet Akçakaya · 2020
Later among the works it cites.
On hallucinations in tomographic image reconstruction
Sayantan Bhadra, Varun A. Kelkar, Frank J. Brooks, and Mark A. Anastasio · 2021
Later among the works it cites.
Measuring robustness in deep learning based compressive sensing
Mohammad Zalbagi Darestani, Akshay S. Chaudhari, and Reinhard Heckel · 2021
Later among the works it cites.
Accelerated MRI with un-trained neural networks
Mohammad Zalbagi Darestani and Reinhard Heckel · 2021
Later among the works it cites.
Bilevel Optimization Methods in Imaging
Juan Carlos De los Reyes and David Villacís · 2021
Later among the works it cites.
Deep equilibrium architectures for inverse problems in imaging
Davis Gilton, Gregory Ongie, and Rebecca Willett · 2021
Later among the works it cites.
Model adaptation for inverse problems in imaging
Davis Gilton, Gregory Ongie, and Rebecca Willett · 2021
Later among the works it cites.
Deep model-based magnetic resonance parameter mapping network (DOPAMINE) for fast T1 mapping using variable flip angle method
Yohan Jun, Hyungseob Shin, Taejoon Eo, Taeseong Kim, and Dosik Hwang · 2021
Later among the works it cites.
An end-to-end-trainable iterative network architecture for accelerated radial multi-coil 2D cine MR image reconstruction
Andreas Kofler, Markus Haltmeier, Tobias Schaeffter, and Christoph Kolbitsch · 2021
Later among the works it cites.
Deep learning–enhanced T1 mapping with spatial-temporal and physical constraint
Yuze Li, Yajie Wang, Haikun Qi, Zhangxuan Hu, Zhensen Chen, Runyu Yang, Huiyu Qiao, Jie Sun, Tao Wang, Xihai Zhao, et al · 2021
Later among the works it cites.
Magnetic resonance parameter mapping using model-guided self-supervised deep learning
Fang Liu, Richard Kijowski, Georges El Fakhri, and Li Feng · 2021
Later among the works it cites.
Algorithm unrolling: Interpretable, efficient deep learning for signal and image processing
Vishal Monga, Yuelong Li, and Yonina C Eldar · 2021
Later among the works it cites.
Results of the 2020 fastMRI challenge for machine learning MR image reconstruction
Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, et al · 2021
Later among the works it cites.
Adaptive sparsity level and dictionary size estimation for image reconstruction in accelerated 2D radial cine MRI
Marie-Christine Pali, Tobias Schaeffter, Christoph Kolbitsch, and Andreas Kofler · 2021
Later among the works it cites.
On the origin of implicit regularization in stochastic gradient descent
Samuel L Smith, Benoit Dherin, David Barrett, and Soham De · 2021
Later among the works it cites.
Time-dependent deep image prior for dynamic MRI
Jaejun Yoo, Kyong Hwan Jin, Harshit Gupta, Jerome Yerly, Matthias Stuber, and Michael Unser · 2021
Later among the works it cites.
Hyperdomainnet: Universal domain adaptation for generative adversarial networks
Aibek Alanov, Vadim Titov, and Dmitry P. Vetrov · 2022
Later among the works it cites.
Multi-coil MRI reconstruction challenge—assessing brain MRI reconstruction models and their generalizability to varying coil configurations
Youssef Beauferris, Jonas Teuwen, Dimitrios Karkalousos, Nikita Moriakov, Matthan Caan, George Yiasemis, Lívia Rodrigues, Alexandre Lopes, Helio Pedrini, Letícia Rittner, et al · 2022
Later among the works it cites.
Bilevel methods for image reconstruction
Caroline Crockett and Jeffrey A Fessler · 2022
Later among the works it cites.
Test-time training can close the natural distribution shift performance gap in deep learning based compressed sensing
Mohammad Zalbagi Darestani, Jiayu Liu, and Reinhard Heckel · 2022
Later among the works it cites.
Optimization with learning-informed differential equation constraints and its applications
Guozhi Dong, Michael Hintermüller, and Kostas Papafitsoros · 2022
Later among the works it cites.
A plug-and-play approach to multiparametric quantitative MRI: image reconstruction using pre-trained deep denoisers
Ketan Fatania, Carolin M Pirkl, Marion I Menzel, Peter Hall, and Mohammad Golbabaee · 2022
Later among the works it cites.
Accurate parameter estimation using scan-specific unsupervised deep learning for relaxometry and MR fingerprinting
Mengze Gao, Huihui Ye, Tae Hyung Kim, Zijing Zhang, Seohee So, and Berkin Bilgic · 2022
Later among the works it cites.
Solving inverse problems with deep neural networks–robustness included?
Martin Genzel, Jan Macdonald, and Maximilian März · 2022
Later among the works it cites.
Accelerated cardiac T1 mapping in four heartbeats with inline MyoMapNet: a deep learning-based T1 estimation approach
Rui Guo, Hossam El-Rewaidy, Salah Assana, Xiaoying Cai, Amine Amyar, Kelvin Chow, Xiaoming Bi, Tuyen Yankama, Julia Cirillo, Patrick Pierce, et al · 2022
Later among the works it cites.
Dualization and automatic distributed parameter selection of total generalized variation via bilevel optimization
Michael Hintermüller, Kostas Papafitsoros, Carlos N. Rautenberg, and Hongpeng Sun · 2022
Later among the works it cites.
The more the merrier?—on the number of trainable parameters in iterative neural networks for image reconstruction
Andreas Kofler, Tobias Schaeffter, and Christoph Kolbitsch · 2022
Later among the works it cites.
Convolutional analysis operator learning by end-to-end training of iterative neural networks
Andreas Kofler, Christian Wald, Tobias Schaeffter, Markus Haltmeier, and Christoph Kolbitsch · 2022
Later among the works it cites.
Convolutional dictionary learning by end-to-end training of iterative neural networks
Andreas Kofler, Christian Wald, Tobias Schaeffter, Markus Haltmeier, and Christoph Kolbitsch · 2022
Later among the works it cites.
Bilevel training schemes in imaging for total-variation-type functionals with convex integrands
Valerio Pagliari, Kostas Papafitsoros, Bogdan Raita, and Andreas Vikelis · 2022
Later among the works it cites.
Report on the AAPM deep-learning sparse-view CT grand challenge
Emil Y. Sidky and Xiaochuan Pan · 2022
Later among the works it cites.
CoRRECT: A deep unfolding framework for motion-corrected quantitative R2* mapping
Xiaojian Xu, Weijie Gan, Satya VVN Kothapalli, Dmitriy A Yablonskiy, and Ulugbek S Kamilov · 2022
Later among the works it cites.
A survey on mapping of urban green spaces within remote sensing data using machine learning & deep learning techniques
Smita Sunil Burrewar, Mazharul Haque, and Tanwir Uddin Haider · 2023
Later among the works it cites.
Unsupervised reconstruction of accelerated cardiac cine MRI using neural fields
Tabita Catalán, Matías Courdurier, Axel Osses, René Botnar, Francisco Sahli Costabal, and Claudia Prieto · 2023
Later among the works it cites.
A scan-specific unsupervised method for parallel MRI reconstruction via implicit neural representation
Ruimin Feng, Qing Wu, Yuyao Zhang, and Hongjiang Wei · 2023
Later among the works it cites.
Neural-network-based regularization methods for inverse problems in imaging
Andreas Habring and Martin Holler · 2023
Later among the works it cites.
Plug-and-play methods for integrating physical and learned models in computational imaging: Theory, algorithms, and applications
Ulugbek S Kamilov, Charles A Bouman, Gregery T Buzzard, and Brendt Wohlberg · 2023
Later among the works it cites.
Learning regularization parameter-maps for variational image reconstruction using deep neural networks and algorithm unrolling
Andreas Kofler, Fabian Altekrüger, Fatima Antarou Ba, Christoph Kolbitsch, Evangelos Papoutsellis, David Schote, Clemens Sirotenko, Felix Frederik Zimmermann, and Kostas Papafitsoros · 2023
Later among the works it cites.
Quantitative MR image reconstruction using parameter-specific dictionary learning with adaptive dictionary-size and sparsity-level choice
Andreas Kofler, Kirsten Miriam Kerkering, Laura Göschel, Ariane Fillmer, and Christoph Kolbitsch · 2023
Later among the works it cites.
Deep supervised dictionary learning by algorithm unrolling–Application to fast 2D dynamic MR image reconstruction
Andreas Kofler, Marie-Christine Pali, Tobias Schaeffter, and Christoph Kolbitsch · 2023
Later among the works it cites.
A theoretical framework for self-supervised MR image reconstruction using sub-sampling via variable density noisier2noise
Charles Millard and Mark Chiew · 2023
Later among the works it cites.
Learned Reconstruction Methods With Convergence Guarantees: A survey of concepts and applications
Subhadip Mukherjee, Andreas Hauptmann, Ozan Oktem, Marcelo Pereyra, and Carola-Bibiane Schonlieb · 2023
Later among the works it cites.
MAP-informed unrolled algorithms for hyper-parameter estimation
Pascal Nguyen, Emmanuel Soubies, and Caroline Chaux · 2023
Later among the works it cites.
Dictionary learning–from local towards global and adaptive
Marie-Christine Pali and Karin Schnass · 2023
Later among the works it cites.
On and beyond total variation regularization in imaging: The role of space variance
Monica Pragliola, Luca Calatroni, Alessandro Lanza, and Fiorella Sgallari · 2023
Later among the works it cites.
Quantitative MRI by nonlinear inversion of the Bloch equations
Nick Scholand, Xiaoqing Wang, Volkert Roeloffs, Sebastian Rosenzweig, and Martin Uecker · 2023
Later among the works it cites.
Model-based deep learning
Nir Shlezinger, Jay Whang, Yonina C. Eldar, and Alexandros G. Dimakis · 2023
Later among the works it cites.
K2s challenge: From undersampled k-space to automatic segmentation
Aniket A. Tolpadi, Upasana Bharadwaj, Kenneth T. Gao, Rupsa Bhattacharjee, Felix G. Gassert, Johanna Luitjens, Paula Giesler, Jan Nikolas Morshuis, Paul Fischer, Matthias Hein, et al · 2023
Later among the works it cites.
Cmrxrecon: An open cardiac mri dataset for the competition of accelerated image reconstruction
Chengyan Wang, Jun Lyu, Shuo Wang, Chen Qin, Kunyuan Guo, Xinyu Zhang, Xiaotong Yu, Yan Li, Fanwen Wang, Jianhua Jin, et al · 2023
Later among the works it cites.
DDM 2 : Self-supervised diffusion MRI denoising with generative diffusion models
Tiange Xiang, Mahmut Yurt, Ali B Syed, Kawin Setsompop, and Akshay Chaudhari · 2023
Later among the works it cites.
Deep cardiac MRI reconstruction with ADMM
George Yiasemis, Nikita Moriakov, Jan-Jakob Sonke, and Jonas Teuwen · 2023
Later among the works it cites.
PINQI: An end-to-end physics-informed approach to learned quantitative MRI reconstruction
Felix F Zimmermann, Christoph Kolbitsch, Patrick Schuenke, and Andreas Kofler · 2023
Later among the works it cites.
NoSENSE: Learned unrolled cardiac MRI reconstruction without explicit sensitivity maps
Felix Frederik Zimmermann and Andreas Kofler · 2023
Later among the works it cites.
Felix Frederik Zimmermann, Andreas Kofler, Christoph Kolbitsch, and Patrick Schuenke · 2023
Later among the works it cites.
Joint MAPLE: Accelerated joint T1 and T2* mapping with scan-specific self-supervised networks
Amir Heydari, Abbas Ahmadi, Tae Hyung Kim, and Berkin Bilgic · 2024
Closest in time.