| Machine learning analysis of whole mouse brain vasculature MI Todorov, JC Paetzold, O Schoppe, G Tetteh, S Shit, V Efremov, ... Nature Methods 17 (4), 442-449, 2020 | 347* | 2020 |
| VerSe: A vertebrae labelling and segmentation benchmark for multi-detector CT images A Sekuboyina, ME Husseini, A Bayat, M Löffler, H Liebl, H Li, G Tetteh, ... Medical Image Analysis, 102166, 2021 | 338* | 2021 |
| clDice-a novel topology-preserving loss function for tubular structure segmentation S Shit*, JC Paetzold*, A Sekuboyina, I Ezhov, A Unger, A Zhylka, ... Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021 | 326 | 2021 |
| An automatic multi-tissue human fetal brain segmentation benchmark using the Fetal Tissue Annotation Dataset K Payette, P de Dumast, H Kebiri, I Ezhov, JC Paetzold, S Shit, A Iqbal, ... Scientific Data 8 (1), 1-14, 2021 | 137* | 2021 |
| Shape-aware complementary-task learning for multi-organ segmentation F Navarro*, S Shit*, I Ezhov, J Paetzold, A Gafita, JC Peeken, SE Combs, ... International Workshop on Machine Learning in Medical Imaging, 620-627, 2019 | 82* | 2019 |
| Red-GAN: Attacking class imbalance via conditioned generation. Yet another perspective on medical image synthesis for skin lesion dermoscopy and brain tumor MRI. AB Qasim, I Ezhov, S Shit, O Schoppe, JC Paetzold, A Sekuboyina, ... Proceedings of Machine Learning Research 1, 14, 2020 | 76* | 2020 |
| Comparing methods of detecting and segmenting unruptured intracranial aneurysms on TOF-MRAS: The ADAM challenge KM Timmins, IC van der Schaaf, E Bennink, YM Ruigrok, X An, ... NeuroImage 238, 118216, 2021 | 71 | 2021 |
| Are we using appropriate segmentation metrics? Identifying correlates of human expert perception for CNN training beyond rolling the DICE coefficient F Kofler, I Ezhov, F Isensee, F Balsiger, C Berger, M Koerner, J Paetzold, ... The Journal of Machine Learning for Biomedical Imaging 2 (3), 2023 | 61* | 2023 |
| Relationformer: A unified framework for image-to-graph generation S Shit*, R Koner*, B Wittmann, J Paetzold, I Ezhov, H Li, J Pan, ... 17th European Conference on Computer Vision–ECCV 2022, Tel Aviv, Israel …, 2022 | 61 | 2022 |
| Human emotion recognition from facial thermal image based on fused statistical feature and multi-class SVM A Basu, A Routray, S Shit, AK Deb 2015 Annual IEEE India Conference (INDICON), 1-5, 2015 | 58* | 2015 |
| Topologically faithful image segmentation via induced matching of persistence barcodes N Stucki*, JC Paetzold*, S Shit*, B Menze, U Bauer International Conference on Machine Learning, 32698-32727, 2023 | 50* | 2023 |
| AutoImplant 2020-first MICCAI challenge on automatic cranial implant design J Li, P Pimentel, A Szengel, M Ehlke, H Lamecker, S Zachow, L Estacio, ... IEEE transactions on medical imaging 40 (9), 2329-2342, 2021 | 49 | 2021 |
| Whole Brain Vessel Graphs: A Dataset and Benchmark for Graph Learning and Neuroscience JC Paetzold, J McGinnis, S Shit, I Ezhov, P Büschl, C Prabhakar, ... NeurIPS Dataset 2021, 2021 | 40* | 2021 |
| Infrared imaging based hyperventilation monitoring through respiration rate estimation A Basu, A Routray, R Mukherjee, S Shit Infrared Physics & Technology 77, 382-390, 2016 | 39 | 2016 |
| Relation transformer network R Koner, S Shit, V Tresp arXiv preprint arXiv:2004.06193, 2020 | 36 | 2020 |
| Self-Supervised Pretext Tasks in Model Robustness & Generalizability: A Revisit from Medical Imaging Perspective F Navarro, C Watanabe, S Shit, A Sekuboyina, JC Peeken, SE Combs, ... 2022 44th Annual International Conference of the IEEE Engineering in …, 2022 | 35* | 2022 |
| Geometry-aware neural solver for fast Bayesian calibration of brain tumor models I Ezhov, T Mot, S Shit, J Lipkova, JC Paetzold, F Kofler, C Pellegrini, ... IEEE Transactions on Medical Imaging, 2021 | 27* | 2021 |
| Learn-Morph-Infer: a new way of solving the inverse problem for brain tumor modeling I Ezhov, K Scibilia, K Franitza, F Steinbauer, S Shit, L Zimmer, J Lipkova, ... Medical Image Analysis 83, 102672, 2023 | 26 | 2023 |
| Neural parameters estimation for brain tumor growth modeling I Ezhov, J Lipkova, S Shit, F Kofler, N Collomb, B Lemasson, E Barbier, ... MICCAI 2019, 787-795, 2019 | 25 | 2019 |
| Training-free, single-image super-resolution using a dynamic convolutional network A Bhowmik*, S Shit*, CS Seelamantula IEEE Signal Processing Letters 25 (1), 85-89, 2017 | 24 | 2017 |
Johannes C. PaetzoldImperial College LondonPatvirtintas el. paštas ic.ac.uk