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ORCIDFlorian Knoll
Person information
- affiliation: New York University School of Medicine, New York City, NY, USA
- affiliation (PhD): Graz University of Technology, Austria
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2020 – today
- 2024
[c10]Moritz Zaiss, Junaid R. Rajput, Hoai Nam Dang, Vladimir Golkov, Daniel Cremers, Florian Knoll, Andreas K. Maier:
Exploring GPT-4 as MR Sequence and Reconstruction Programming Assistant - GPT4MR. Bildverarbeitung für die Medizin 2024: 94-99- [c9]Florian Fürnrohr
, Jens Wetzl, Marc Vornehm, Daniel Giese, Florian Knoll:
Data Consistent Variational Networks for Zero-shot Self-supervised MR Reconstruction. Bildverarbeitung für die Medizin 2024: 316-321 - [c8]Junaid R. Rajput, Simon Weinmueller, Jonathan Endres, Peter Dawood, Florian Knoll, Andreas K. Maier, Moritz Zaiss:
Death by Retrospective Undersampling - Caveats and Solutions for Learning-Based MRI Reconstructions. MICCAI (7) 2024: 233-241 - [i16]Jinho Kim, Marcel Dominik Nickel, Florian Knoll:
Accelerated MR Cholangiopancreatography with Deep Learning-based Reconstruction. CoRR abs/2405.03732 (2024) - [i15]Eddy Solomon, Patricia M. Johnson, Zhengguo Tan, Radhika Tibrewala, Yvonne W. Lui, Florian Knoll, Linda Moy, Sungheon Gene Kim, Laura Heacock:
fastMRI Breast: A publicly available radial k-space dataset of breast dynamic contrast-enhanced MRI. CoRR abs/2406.05270 (2024) - 2023
- [j13]Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya:
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging: Combining physics and machine learning for improved medical imaging. IEEE Signal Process. Mag. 40(1): 98-114 (2023) - [j12]Martin Zach, Florian Knoll, Thomas Pock:
Stable Deep MRI Reconstruction Using Generative Priors. IEEE Trans. Medical Imaging 42(12): 3817-3832 (2023) - 2022
- [j11]Marcelo Victor Wüst Zibetti, Florian Knoll, Ravinder R. Regatte:
Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications. IEEE Trans. Computational Imaging 8: 449-461 (2022) - [j10]Dominik Narnhofer, Alexander Effland, Erich Kobler, Kerstin Hammernik, Florian Knoll, Thomas Pock:
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction. IEEE Trans. Medical Imaging 41(2): 279-291 (2022) - [i14]Kerstin Hammernik, Thomas Küstner, Burhaneddin Yaman, Zhengnan Huang, Daniel Rueckert, Florian Knoll, Mehmet Akçakaya:
Physics-Driven Deep Learning for Computational Magnetic Resonance Imaging. CoRR abs/2203.12215 (2022) - [i13]Martin Zach, Florian Knoll, Thomas Pock:
Stable deep MRI reconstruction using Generative Priors. CoRR abs/2210.13834 (2022) - 2021
- [j9]Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, Simon Arberet, Dominik Nickel, Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck, Jonas Teuwen, Dimitrios Karkalousos, Chaoping Zhang, Anuroop Sriram, Zhengnan Huang, Nafissa Yakubova, Yvonne W. Lui, Florian Knoll:
Results of the 2020 fastMRI Challenge for Machine Learning MR Image Reconstruction. IEEE Trans. Medical Imaging 40(9): 2306-2317 (2021) - [c7]Patricia M. Johnson, Geunu Jeong, Kerstin Hammernik, Jo Schlemper, Chen Qin, Jinming Duan, Daniel Rueckert, Jingu Lee, Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen Hendrikus Franciscus Van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring, Eric Z. Chen, Puyang Wang, Xiao Chen, Terrence Chen, Vishal M. Patel, Shanhui Sun, Hyungseob Shin, Yohan Jun, Taejoon Eo, Sewon Kim, Taeseong Kim, Dosik Hwang, Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan W. A. Caan, Max Welling, Matthew J. Muckley, Florian Knoll:
Evaluation of the Robustness of Learned MR Image Reconstruction to Systematic Deviations Between Training and Test Data for the Models from the fastMRI Challenge. MLMIR@MICCAI 2021: 25-34 - [c6]Zhengnan Huang, Jonghyun Bae, Patricia M. Johnson, Terlika Sood, Laura Heacock, Justin Fogarty, Linda Moy, Sungheon Gene Kim, Florian Knoll:
A Simulation Pipeline to Generate Realistic Breast Images for Learning DCE-MRI Reconstruction. MLMIR@MICCAI 2021: 45-53 - [i12]Dominik Narnhofer, Alexander Effland, Erich Kobler, Kerstin Hammernik, Florian Knoll, Thomas Pock:
Bayesian Uncertainty Estimation of Learned Variational MRI Reconstruction. CoRR abs/2102.06665 (2021) - [i11]Ruiyang Zhao, Burhaneddin Yaman, Yuxin Zhang, Russell Stewart, Austin Dixon, Florian Knoll, Zhengnan Huang, Yvonne W. Lui, Michael S. Hansen, Matthew P. Lungren:
fastMRI+: Clinical Pathology Annotations for Knee and Brain Fully Sampled Multi-Coil MRI Data. CoRR abs/2109.03812 (2021) - [i10]Marcelo V. W. Zibetti, Florian Knoll, Ravinder R. Regatte:
Alternating Learning Approach for Variational Networks and Undersampling Pattern in Parallel MRI Applications. CoRR abs/2110.14703 (2021) - 2020
- [j8]Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya:
Deep-Learning Methods for Parallel Magnetic Resonance Imaging Reconstruction: A Survey of the Current Approaches, Trends, and Issues. IEEE Signal Process. Mag. 37(1): 128-140 (2020) - [c5]Anuroop Sriram, Jure Zbontar, Tullie Murrell, Aaron Defazio, C. Lawrence Zitnick, Nafissa Yakubova, Florian Knoll, Patricia M. Johnson:
End-to-End Variational Networks for Accelerated MRI Reconstruction. MICCAI (2) 2020: 64-73 - [i9]Florian Knoll, Tullie Murrell, Anuroop Sriram, Nafissa Yakubova, Jure Zbontar, Michael G. Rabbat, Aaron Defazio, Matthew J. Muckley, Daniel K. Sodickson, C. Lawrence Zitnick, Michael P. Recht:
Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge. CoRR abs/2001.02518 (2020) - [i8]Anuroop Sriram, Jure Zbontar, Tullie Murrell, Aaron Defazio, C. Lawrence Zitnick, Nafissa Yakubova, Florian Knoll, Patricia M. Johnson:
End-to-End Variational Networks for Accelerated MRI Reconstruction. CoRR abs/2004.06688 (2020) - [i7]Oliver Maier, Steven H. Baete, Alexander Fyrdahl, Kerstin Hammernik, Seb Harrevelt, Lars Kasper, Agah Karakuzu, Michael Loecher, Franz Patzig, Ye Tian, Ke Wang, Daniel Gallichan, Martin Uecker, Florian Knoll:
CG-SENSE revisited: Results from the first ISMRM reproducibility challenge. CoRR abs/2008.04308 (2020) - [i6]Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, Simon Arberet, Dominik Nickel, Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck, Jonas Teuwen, Dimitrios Karkalousos, Chaoping Zhang, Anuroop Sriram, Zhengnan Huang, Nafissa Yakubova, Yvonne W. Lui, Florian Knoll:
State-of-the-Art Machine Learning MRI Reconstruction in 2020: Results of the Second fastMRI Challenge. CoRR abs/2012.06318 (2020)
2010 – 2019
- 2019
- [c4]Patricia M. Johnson, Matthew J. Muckley, Mary Bruno, Erich Kobler, Kerstin Hammernik, Thomas Pock, Florian Knoll:
Joint Multi-anatomy Training of a Variational Network for Reconstruction of Accelerated Magnetic Resonance Image Acquisitions. MLMIR@MICCAI 2019: 71-79 - [e2]Florian Knoll, Andreas Maier, Daniel Rueckert, Jong Chul Ye:
Machine Learning for Medical Image Reconstruction - Second International Workshop, MLMIR 2019, Held in Conjunction with MICCAI 2019, Shenzhen, China, October 17, 2019, Proceedings. Lecture Notes in Computer Science 11905, Springer 2019, ISBN 978-3-030-33842-8 [contents] - [i5]Florian Knoll, Kerstin Hammernik, Chi Zhang, Steen Moeller, Thomas Pock, Daniel K. Sodickson, Mehmet Akçakaya:
Deep Learning Methods for Parallel Magnetic Resonance Image Reconstruction. CoRR abs/1904.01112 (2019) - 2018
- [j7]Georg Schramm, Martin Holler, Ahmadreza Rezaei, Kathleen Vunckx, Florian Knoll, Kristian Bredies, Fernando E. Boada, Johan Nuyts:
Evaluation of Parallel Level Sets and Bowsher's Method as Segmentation-Free Anatomical Priors for Time-of-Flight PET Reconstruction. IEEE Trans. Medical Imaging 37(2): 590-603 (2018) - [c3]Erich Kobler, Matthew J. Muckley, Baiyu Chen, Florian Knoll, Kerstin Hammernik, Thomas Pock, Daniel K. Sodickson, Ricardo Otazo:
Variational Deep Learning for Low-Dose Computed Tomography. ICASSP 2018: 6687-6691 - [e1]Florian Knoll, Andreas K. Maier, Daniel Rueckert:
Machine Learning for Medical Image Reconstruction - First International Workshop, MLMIR 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16, 2018, Proceedings. Lecture Notes in Computer Science 11074, Springer 2018, ISBN 978-3-030-00128-5 [contents] - [i4]Sunli Tang, Carlos Fernandez-Granda, Sylvain Lannuzel, Brett Bernstein, Riccardo Lattanzi, Martijn A. Cloos, Florian Knoll, Jakob Assländer:
Multicompartment Magnetic Resonance Fingerprinting. CoRR abs/1802.10492 (2018) - [i3]Jure Zbontar, Florian Knoll, Anuroop Sriram, Matthew J. Muckley, Mary Bruno, Aaron Defazio, Marc Parente, Krzysztof J. Geras, Joe Katsnelson, Hersh Chandarana, Zizhao Zhang, Michal Drozdzal, Adriana Romero, Michael G. Rabbat, Pascal Vincent, James Pinkerton, Duo Wang, Nafissa Yakubova, Erich Owens, C. Lawrence Zitnick, Michael P. Recht, Daniel K. Sodickson, Yvonne W. Lui:
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI. CoRR abs/1811.08839 (2018) - 2017
- [j6]Florian Knoll, Martin Holler, Thomas Kösters, Ricardo Otazo, Kristian Bredies, Daniel K. Sodickson:
Joint MR-PET Reconstruction Using a Multi-Channel Image Regularizer. IEEE Trans. Medical Imaging 36(1): 1-16 (2017) - [i2]Kerstin Hammernik, Teresa Klatzer, Erich Kobler, Michael P. Recht, Daniel K. Sodickson, Thomas Pock, Florian Knoll:
Learning a Variational Network for Reconstruction of Accelerated MRI Data. CoRR abs/1704.00447 (2017) - 2015
- [c2]Martin Benning, Florian Knoll, Carola-Bibiane Schönlieb, Tuomo Valkonen:
Preconditioned ADMM with Nonlinear Operator Constraint. System Modelling and Optimization 2015: 117-126 - [c1]Daniel K. Sodickson, Li Feng, Florian Knoll, Martijn A. Cloos, Noam Ben-Eliezer, Leon Axel, Hersh Chandarana, Tobias Block, Ricardo Otazo:
The rapid imaging renaissance: sparser samples, denser dimensions, and glimmerings of a grand unified tomography. Medical Imaging: Biomedical Applications in Molecular, Structural, and Functional Imaging 2015: 94170G - 2014
- [j5]Tilman J. Sumpf, Andreas Petrovic, Martin Uecker, Florian Knoll, Jens Frahm:
Fast T2 Mapping With Improved Accuracy Using Undersampled Spin-Echo MRI and Model-Based Reconstructions With a Generating Function. IEEE Trans. Medical Imaging 33(12): 2213-2222 (2014) - [i1]Tilman J. Sumpf, Andreas Petrovic, Martin Uecker, Florian Knoll, Jens Frahm:
Fast T2 Mapping with Improved Accuracy Using Undersampled Spin-echo MRI and Model-based Reconstructions with a Generating Function. CoRR abs/1405.3574 (2014) - 2013
- [j4]Manuel Freiberger, Florian Knoll, Kristian Bredies, Hermann Scharfetter, Rudolf Stollberger:
The Agile Library for Biomedical Image Reconstruction Using GPU Acceleration. Comput. Sci. Eng. 15(1): 34-44 (2013) - [j3]Tuomo Valkonen, Kristian Bredies, Florian Knoll:
Total Generalized Variation in Diffusion Tensor Imaging. SIAM J. Imaging Sci. 6(1): 487-525 (2013) - 2012
- [j2]Stephen L. Keeling, Christian Clason, Michael Hintermüller, Florian Knoll, Antoine Laurain, Gregory von Winckel:
An image space approach to Cartesian based parallel MR imaging with total variation regularization. Medical Image Anal. 16(1): 189-200 (2012) - 2011
- [j1]Stephen L. Keeling, Michael Hintermüller, Florian Knoll, Daniel Kraft, Antoine Laurain:
A total variation based approach to correcting surface coil magnetic resonance images. Appl. Math. Comput. 218(2): 219-232 (2011)
Coauthor Index
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