| 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 | 687 | 2018 |
| 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 | 251 | 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 | 191* | 2021 |
| 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 | 159 | 2020 |
| Reducing Uncertainty in Undersampled MRI Reconstruction with Active Acquisition Z Zhang, A Romero, MJ Muckley, P Vincent, L Yang, M Drozdzal Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2019 | 110 | 2019 |
| 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 | 100 | 2020 |
| COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction A Sriram, M Muckley, K Sinha, F Shamout, J Pineau, KJ Geras, L Azour, ... arXiv preprint arXiv:2101.04909, 2021 | 64 | 2021 |
| Training a Neural Network for Gibbs and Noise Removal in Diffusion MRI MJ Muckley, B Ades-Aron, A Papaioannou, G Lemberskiy, E Solomon, ... Magnetic Resonance in Medicine 85 (1), 413-428, 2021 | 43 | 2021 |
| TorchKbNufft: A High‐Level, Hardware‐Agnostic Non‐Uniform Fast Fourier Transform MJ Muckley, R Stern, T Murrell, F Knoll ISMRM Workshop on Data Sampling & Image Reconstruction, 2020 | 41 | 2020 |
| Fast parallel MR image reconstruction via B1-based, adaptive restart, iterative soft thresholding algorithms (BARISTA) MJ Muckley, DC Noll, JA Fessler IEEE Transactions on Medical Imaging 34 (2), 578-588, 2015 | 36 | 2015 |
| Spectroscopic visualization of nanoscale deformation in bone: interaction of light with partially disordered nanostructure Z Xu, X Sun, J Liu, Q Song, MJ Muckley, O Akkus, YL Kim Journal of Biomedical Optics 15 (6), 060503, 2010 | 23 | 2010 |
| The morphological, material-level, and ash properties of turkey femurs from 3 different genetic strains during production Z Zhong, MJ Muckley, S Agcaoglu, ME Grisham, H Zhao, M Orth, ... Poultry Science 91 (11), 2736-2746, 2012 | 13 | 2012 |
| Deep learning reconstruction enables prospectively accelerated clinical knee MRI PM Johnson, DJ Lin, J Zbontar, CL Zitnick, A Sriram, M Muckley, JS Babb, ... Radiology 307 (2), e220425, 2023 | 12 | 2023 |
| Variational Deep Learning for Low-Dose Computed Tomography E Kobler, M Muckley, B Chen, F Knoll, K Hammernik, T Pock, D Sodickson, ... Proceedings of the IEEE International Conference on Acoustics, Speech and …, 2018 | 12 | 2018 |
| Estrogen depletion and drug treatment alter the microstructure of type I collagen in bone MA Cauble, MJ Muckley, M Fang, JA Fessler, K Welch, ED Rothman, ... Bone Reports 5, 243-251, 2016 | 11 | 2016 |
| Image Compression with Product Quantized Masked Image Modeling A El-Nouby, MJ Muckley, K Ullrich, I Laptev, J Verbeek, H Jégou Transactions on Machine Learning Research, 2023 | 10 | 2023 |
| On learning adaptive acquisition policies for undersampled multi-coil MRI reconstruction T Bakker, M Muckley, A Romero-Soriano, M Drozdzal, L Pineda International Conference on Medical Imaging with Deep Learning, 63-85, 2022 | 10 | 2022 |
| Image reconstruction for interrupted-beam x-ray CT on diagnostic clinical scanners MJ Muckley, B Chen, T Vahle, T O’Donnell, F Knoll, AD Sodickson, ... Physics in Medicine & Biology 64 (15), 155007, 2019 | 10 | 2019 |
| Evaluation of the robustness of learned MR image reconstruction to systematic deviations between training and test data for the models from the fastMRI challenge PM Johnson, G Jeong, K Hammernik, J Schlemper, C Qin, J Duan, ... Machine Learning for Medical Image Reconstruction: 4th International …, 2021 | 9 | 2021 |
| SparseCT: System concept and design of multislit collimators B Chen, E Kobler, MJ Muckley, AD Sodickson, T O'Donnell, T Flohr, ... Medical Physics 46 (6), 2589-2599, 2019 | 9 | 2019 |
Florian KnollFriedrich-Alexander University Erlangen NurembergVerified email at fau.de
