| Ilastik: Interactive learning and segmentation toolkit C Sommer, C Straehle, U Koethe, FA Hamprecht 2011 IEEE international symposium on biomedical imaging: From nano to macro …, 2011 | 1167 | 2011 |
| Ilastik: interactive machine learning for (bio) image analysis S Berg, D Kutra, T Kroeger, CN Straehle, BX Kausler, C Haubold, ... Nature methods 16 (12), 1226-1232, 2019 | 755 | 2019 |
| Analyzing inverse problems with invertible neural networks L Ardizzone, J Kruse, S Wirkert, D Rahner, EW Pellegrini, RS Klessen, ... arXiv preprint arXiv:1808.04730, 2018 | 290 | 2018 |
| On oblique random forests BH Menze, BM Kelm, DN Splitthoff, U Koethe, FA Hamprecht Joint European Conference on Machine Learning and Knowledge Discovery in …, 2011 | 268 | 2011 |
| Learning to count with regression forest and structured labels L Fiaschi, U Köthe, R Nair, FA Hamprecht Proceedings of the 21st international conference on pattern recognition …, 2012 | 229 | 2012 |
| Edge and junction detection with an improved structure tensor U Köthe Joint Pattern Recognition Symposium, 25-32, 2003 | 226 | 2003 |
| Automated detection and segmentation of synaptic contacts in nearly isotropic serial electron microscopy images A Kreshuk, CN Straehle, C Sommer, U Koethe, M Cantoni, G Knott, ... PloS one 6 (10), e24899, 2011 | 148 | 2011 |
| Guided image generation with conditional invertible neural networks L Ardizzone, C Lüth, J Kruse, C Rother, U Köthe arXiv preprint arXiv:1907.02392, 2019 | 143 | 2019 |
| Segmentation of SBFSEM volume data of neural tissue by hierarchical classification B Andres, U Köthe, M Helmstaedter, W Denk, FA Hamprecht Joint Pattern Recognition Symposium, 142-152, 2008 | 134 | 2008 |
| Theoretical and experimental error analysis of continuous-wave time-of-flight range cameras M Frank, M Plaue, H Rapp, U Köthe, B Jähne, FA Hamprecht Optical Engineering 48 (1), 013602, 2009 | 133 | 2009 |
| Multicut brings automated neurite segmentation closer to human performance T Beier, C Pape, N Rahaman, T Prange, S Berg, DD Bock, A Cardona, ... Nature methods 14 (2), 101-102, 2017 | 125 | 2017 |
| Probabilistic image segmentation with closedness constraints B Andres, JH Kappes, T Beier, U Köthe, FA Hamprecht 2011 International Conference on Computer Vision, 2611-2618, 2011 | 116 | 2011 |
| Globally optimal closed-surface segmentation for connectomics B Andres, T Kroeger, KL Briggman, W Denk, N Korogod, G Knott, ... European Conference on Computer Vision, 778-791, 2012 | 115 | 2012 |
| Graphical model for joint segmentation and tracking of multiple dividing cells M Schiegg, P Hanslovsky, C Haubold, U Koethe, L Hufnagel, ... Bioinformatics 31 (6), 948-956, 2015 | 97 | 2015 |
| Toward digital staining using imaging mass spectrometry and random forests M Hanselmann, U Kothe, M Kirchner, BY Renard, ER Amstalden, ... Journal of proteome research 8 (7), 3558-3567, 2009 | 90 | 2009 |
| Integrated Edge and Junction Detection with the Boundary Tensor. U Köthe ICCV 3, 424-431, 2003 | 85 | 2003 |
| DALSA: domain adaptation for supervised learning from sparsely annotated MR images M Goetz, C Weber, F Binczyk, J Polanska, R Tarnawski, ... IEEE transactions on medical imaging 35 (1), 184-196, 2015 | 73 | 2015 |
| Disentanglement by nonlinear ica with general incompressible-flow networks (gin) P Sorrenson, C Rother, U Köthe arXiv preprint arXiv:2001.04872, 2020 | 72 | 2020 |
| Automated detection of synapses in serial section transmission electron microscopy image stacks A Kreshuk, U Koethe, E Pax, DD Bock, FA Hamprecht PloS one 9 (2), e87351, 2014 | 67 | 2014 |
| 3D segmentation of SBFSEM images of neuropil by a graphical model over supervoxel boundaries B Andres, U Koethe, T Kroeger, M Helmstaedter, KL Briggman, W Denk, ... Medical image analysis 16 (4), 796-805, 2012 | 65 | 2012 |
Fred A. HamprechtProfessor, Heidelberg UniversityVerified email at iwr.uni-heidelberg.de
