F
Florian Knoll
Researcher at New York University
Publications - 132
Citations - 6373
Florian Knoll is an academic researcher from New York University. The author has contributed to research in topics: Iterative reconstruction & Computer science. The author has an hindex of 29, co-authored 120 publications receiving 4090 citations. Previous affiliations of Florian Knoll include Greifswald University Hospital & West Coast University.
Papers
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Journal ArticleDOI
Learning a variational network for reconstruction of accelerated MRI data.
Kerstin Hammernik,Teresa Klatzer,Erich Kobler,Michael P. Recht,Daniel K. Sodickson,Thomas Pock,Thomas Pock,Florian Knoll +7 more
TL;DR: In this paper, a variational network approach is proposed to reconstruct the clinical knee imaging protocol for different acceleration factors and sampling patterns using retrospectively and prospectively undersampled data.
Journal ArticleDOI
Second order total generalized variation (TGV) for MRI
TL;DR: This work introduces the new concept of total generalized variation for magnetic resonance imaging, a new mathematical framework, which is a generalization of the total variation theory and which eliminates these restrictions.
Posted Content
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI.
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 James Owens,C. Lawrence Zitnick,Michael P. Recht,Daniel K. Sodickson,Yvonne W. Lui +22 more
TL;DR: The fastMRI dataset is introduced, a large-scale collection of both raw MR measurements and clinical MR images that can be used for training and evaluation of machine-learning approaches to MR image reconstruction.
Posted Content
Learning a Variational Network for Reconstruction of Accelerated MRI Data
Kerstin Hammernik,Teresa Klatzer,Erich Kobler,Michael P. Recht,Daniel K. Sodickson,Thomas Pock,Thomas Pock,Florian Knoll +7 more
TL;DR: To allow fast and high‐quality reconstruction of clinical accelerated multi‐coil MR data by learning a variational network that combines the mathematical structure of variational models with deep learning.
Journal ArticleDOI
fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning.
Florian Knoll,Jure Zbontar,Anuroop Sriram,Matthew J. Muckley,Mary Bruno,Aaron Defazio,Marc Parente,Krzysztof J. Geras,Joe Katsnelson,Hersh Chandarana,Zizhao Zhang,Michal Drozdzalv,Adriana Romero,Michael G. Rabbat,Pascal Vincent,James Pinkerton,Duo Wang,Nafissa Yakubova,Erich James Owens,C. Lawrence Zitnick,Michael P. Recht,Daniel K. Sodickson,Yvonne W. Lui +22 more
TL;DR: A publicly available dataset containing k-space data as well as Digital Imaging and Communications in Medicine image data of knee images for accelerated MR image reconstruction using machine learning is presented.