Florian Knoll

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Daniel SodicksonChief of Innovation, Department of Radiology, New York University Grossman School of MedicineDirección de correo verificada de med.nyu.edu
Kerstin HammernikNVIDIADirección de correo verificada de nvidia.com
Thomas PockProfessor of Computer Science, TU GrazDirección de correo verificada de icg.tugraz.at
Rudolf StollbergerGraz University of TechnologyDirección de correo verificada de tugraz.at
Kristian BrediesUniversity of GrazDirección de correo verificada de uni-graz.at
Matthew MuckleyMeta FAIRDirección de correo verificada de meta.com
Patricia M. JohnsonNew York University Medical CenterDirección de correo verificada de nyulangone.org
Anuroop SriramMeta FAIRDirección de correo verificada de alumni.cmu.edu
Erich KoblerCo-Groupleader at Department of Neuroradiology, University Hospital BonnDirección de correo verificada de uni-bonn.de
Martijn CloosThe University of QueenslandDirección de correo verificada de uq.edu.au
Ricardo OtazoVice-Chair for Research, Department of Medical Physics, Memorial Sloan Kettering Cancer CenterDirección de correo verificada de mskcc.org
Christian ClasonDepartment of Mathematics and Scientific Computing, University of GrazDirección de correo verificada de uni-graz.at
C. Lawrence ZitnickFAIR (Meta)Dirección de correo verificada de fb.com
Jure ZbontarOpenAIDirección de correo verificada de openai.com
Tullie MurrellFacebook AI ResearchDirección de correo verificada de fb.com
Aaron DefazioFundamental AI Research team, Meta NYDirección de correo verificada de anu.edu.au
Kai Tobias BlockNYU Grossman School of MedicineDirección de correo verificada de nyumc.org
Krzysztof J. GerasNew York UniversityDirección de correo verificada de nyu.edu
Michael RabbatResearch Scientist at FacebookDirección de correo verificada de fb.com
Riccardo LattanziProfessor of Radiology, Electrical and Computer Engineering, and Biomedical EngineeringDirección de correo verificada de nyulangone.org

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Florian Knoll

Friedrich-Alexander University Erlangen Nuremberg

Dirección de correo verificada de fau.de - Página principal

Magnetic Resonance Imaging Machine Learning Inverse Problems Image Reconstruction


Título Ordenar por citas Ordenar por año Ordenar por título	Citado por Citado por	Año
Learning a variational network for reconstruction of accelerated MRI data K Hammernik, T Klatzer, E Kobler, MP Recht, DK Sodickson, T Pock, ... Magnetic resonance in medicine 79 (6), 3055-3071, 2018	1787	2018
fastMRI: An open dataset and benchmarks for accelerated MRI J Zbontar, F Knoll, A Sriram, T Murrell, Z Huang, MJ Muckley, A Defazio, ... arXiv preprint arXiv:1811.08839, 2018	875	2018
Second order total generalized variation (TGV) for MRI F Knoll, K Bredies, T Pock, R Stollberger Magnetic resonance in medicine 65 (2), 480-491, 2011	709	2011
fastMRI: A publicly available raw k-space and DICOM dataset of knee images for accelerated MR image reconstruction using machine learning F Knoll, J Zbontar, A Sriram, MJ Muckley, M Bruno, A Defazio, M Parente, ... Radiology: Artificial Intelligence 2 (1), e190007, 2020	367	2020
Deep-learning methods for parallel magnetic resonance imaging reconstruction: A survey of the current approaches, trends, and issues F Knoll, K Hammernik, C Zhang, S Moeller, T Pock, DK Sodickson, ... IEEE signal processing magazine 37 (1), 128-140, 2020	330	2020
End-to-end variational networks for accelerated MRI reconstruction A Sriram, J Zbontar, T Murrell, A Defazio, CL Zitnick, N Yakubova, F Knoll, ... Medical Image Computing and Computer Assisted Intervention–MICCAI 2020: 23rd …, 2020	305	2020
Results of the 2020 fastMRI challenge for machine learning MR image reconstruction MJ Muckley, B Riemenschneider, A Radmanesh, S Kim, G Jeong, J Ko, ... IEEE transactions on medical imaging 40 (9), 2306-2317, 2021	287*	2021
Low rank alternating direction method of multipliers reconstruction for MR fingerprinting J Assländer, MA Cloos, F Knoll, DK Sodickson, J Hennig, R Lattanzi Magnetic resonance in medicine 79 (1), 83-96, 2018	256	2018
Multiparametric imaging with heterogeneous radiofrequency fields MA Cloos, F Knoll, T Zhao, KT Block, M Bruno, GC Wiggins, ... Nature communications 7 (1), 12445, 2016	254	2016
Assessment of the generalization of learned image reconstruction and the potential for transfer learning F Knoll, K Hammernik, E Kobler, T Pock, MP Recht, DK Sodickson Magnetic resonance in medicine 81 (1), 116-128, 2019	235	2019
Advancing machine learning for MR image reconstruction with an open competition: Overview of the 2019 fastMRI challenge F Knoll, T Murrell, A Sriram, N Yakubova, J Zbontar, M Rabbat, A Defazio, ... Magnetic resonance in medicine 84 (6), 3054-3070, 2020	219	2020
Artificial intelligence for MR image reconstruction: an overview for clinicians DJ Lin, PM Johnson, F Knoll, YW Lui Journal of Magnetic Resonance Imaging 53 (4), 1015-1028, 2021	171	2021
Gibbs ringing in diffusion MRI J Veraart, E Fieremans, IO Jelescu, F Knoll, DS Novikov Magnetic resonance in medicine 76 (1), 301-314, 2016	163	2016
Total generalized variation in diffusion tensor imaging T Valkonen, K Bredies, F Knoll SIAM journal on imaging sciences 6 (1), 487-525, 2013	141	2013
Using deep learning to accelerate knee MRI at 3 T: results of an interchangeability study MP Recht, J Zbontar, DK Sodickson, F Knoll, N Yakubova, A Sriram, ... American Journal of Roentgenology 215 (6), 1421-1429, 2020	140	2020
Artificial intelligence in musculoskeletal imaging: current status and future directions S Gyftopoulos, D Lin, F Knoll, AM Doshi, TC Rodrigues, MP Recht American Journal of Roentgenology 213 (3), 506-513, 2019	140	2019
Parallel imaging with nonlinear reconstruction using variational penalties F Knoll, C Clason, K Bredies, M Uecker, R Stollberger Magnetic resonance in medicine 67 (1), 34-41, 2012	135	2012
Joint MR-PET reconstruction using a multi-channel image regularizer F Knoll, M Holler, T Koesters, R Otazo, K Bredies, DK Sodickson IEEE transactions on medical imaging 36 (1), 1-16, 2016	132	2016
gpuNUFFT-an open source GPU library for 3D regridding with direct Matlab interface F Knoll, A Schwarzl, C Diwoky, DK Sodickson Proceedings of the 22nd annual meeting of ISMRM, Milan, Italy 4297, 2014	117	2014
Adapted random sampling patterns for accelerated MRI F Knoll, C Clason, C Diwoky, R Stollberger Magnetic resonance materials in physics, biology and medicine 24, 43-50, 2011	107	2011

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