| Content-aware image restoration: pushing the limits of fluorescence microscopy M Weigert, U Schmidt, T Boothe, A Müller, A Dibrov, A Jain, B Wilhelm, ... Nature methods 15 (12), 1090-1097, 2018 | 717 | 2018 |
| Noise2void-learning denoising from single noisy images A Krull, TO Buchholz, F Jug Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2019 | 670 | 2019 |
| An objective comparison of cell-tracking algorithms V Ulman, M Maška, KEG Magnusson, O Ronneberger, C Haubold, ... Nature methods 14 (12), 1141-1152, 2017 | 449 | 2017 |
| Democratising deep learning for microscopy with ZeroCostDL4Mic L von Chamier, RF Laine, J Jukkala, C Spahn, D Krentzel, E Nehme, ... Nature communications 12 (1), 2276, 2021 | 198 | 2021 |
| ClearVolume: open-source live 3D visualization for light-sheet microscopy LA Royer, M Weigert, U Günther, N Maghelli, F Jug, IF Sbalzarini, ... Nature methods 12 (6), 480-481, 2015 | 139 | 2015 |
| Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison T Vicar, J Balvan, J Jaros, F Jug, R Kolar, M Masarik, J Gumulec BMC bioinformatics 20 (1), 1-25, 2019 | 118 | 2019 |
| Interacting maps for fast visual interpretation M Cook, L Gugelmann, F Jug, C Krautz, A Steger The 2011 International Joint Conference on Neural Networks, 770-776, 2011 | 113 | 2011 |
| Probabilistic Noise2Void: Unsupervised Content-Aware Denoising A Krull, T Vičar, M Prakash, M Lalit, F Jug Frontiers in Computer Science 19, 5, 2020 | 105 | 2020 |
| Monitoring single-cell gene regulation under dynamically controllable conditions with integrated microfluidics and software M Kaiser, F Jug, T Julou, S Deshpande, T Pfohl, OK Silander, G Myers, ... Nature communications 9 (1), 212, 2018 | 95 | 2018 |
| CLIJ: GPU-accelerated image processing for everyone R Haase, LA Royer, P Steinbach, D Schmidt, A Dibrov, U Schmidt, ... Nature methods 17 (1), 5-6, 2020 | 92 | 2020 |
| Differential lateral and basal tension drive folding of Drosophila wing discs through two distinct mechanisms L Sui, S Alt, M Weigert, N Dye, S Eaton, F Jug, EW Myers, F Jülicher, ... Nature communications 9 (1), 4620, 2018 | 91 | 2018 |
| Cryo-care: content-aware image restoration for cryo-transmission electron microscopy data TO Buchholz, M Jordan, G Pigino, F Jug 2019 IEEE 16th International Symposium on Biomedical Imaging (ISBI 2019 …, 2019 | 89 | 2019 |
| Isotropic reconstruction of 3D fluorescence microscopy images using convolutional neural networks M Weigert, L Royer, F Jug, G Myers Medical Image Computing and Computer-Assisted Intervention− MICCAI 2017 …, 2017 | 61 | 2017 |
| The ImageJ ecosystem: Open‐source software for image visualization, processing, and analysis AB Schroeder, ETA Dobson, CT Rueden, P Tomancak, F Jug, KW Eliceiri Protein Science 30 (1), 234-249, 2021 | 56 | 2021 |
| ZeroCostDL4Mic: an open platform to use Deep-Learning in Microscopy L Chamier, RF Laine, J Jukkala, C Spahn, D Krentzel, E Nehme, ... BioRxiv, 2020.03. 20.000133, 2020 | 51 | 2020 |
| Content-aware image restoration for electron microscopy TO Buchholz, A Krull, R Shahidi, G Pigino, G Jékely, F Jug Methods in cell biology 152, 277-289, 2019 | 46 | 2019 |
| 3D FIB-SEM reconstruction of microtubule–organelle interaction in whole primary mouse β cells A Müller, D Schmidt, CS Xu, S Pang, JV D’Costa, S Kretschmar, ... Journal of Cell Biology 220 (2), 2021 | 43 | 2021 |
| Regionalized tissue fluidization is required for epithelial gap closure during insect gastrulation A Jain, V Ulman, A Mukherjee, M Prakash, MB Cuenca, LG Pimpale, ... Nature communications 11 (1), 5604, 2020 | 43* | 2020 |
| Reliable neuronal systems: the importance of heterogeneity J Lengler, F Jug, A Steger PloS one 8 (12), e80694, 2013 | 43 | 2013 |
| DenoiSeg: Joint Denoising and Segmentation TO Buchholz, M Prakash, D Schmidt, A Krull, F Jug Computer Vision–ECCV 2020 Workshops: Glasgow, UK, August 23–28, 2020 …, 2021 | 39 | 2021 |
Gene MyersMax-Planck Institute for Molecular Cell Biology & GeneticsVerified email at mpi-cbg.de
