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Ivan Ezhov
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The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
8022023
clDice-a Topology-Preserving Loss Function for Tubular Structure Segmentation.
S Shit, JC Paetzold, A Sekuboyina, I Ezhov, A Unger, A Zhylka, ...
CVPR, 2021, 2020
151*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 73, 102166, 2021
1442021
A comparison of automatic multi-tissue segmentation methods of the human fetal brain using the FeTA dataset
K Payette, P de Dumast, H Kebiri, I Ezhov, JC Paetzold, S Shit, A Iqbal, ...
Scientific Data, 2021, arXiv: 2010.15526, 2020
86*2020
Federated learning enables big data for rare cancer boundary detection
S Pati, U Baid, B Edwards, M Sheller, SH Wang, GA Reina, P Foley, ...
Nature communications 13 (1), 7346, 2022
852022
BraTS Toolkit: Translating BraTS brain tumor segmentation algorithms into clinical and scientific practice
F Kofler, C Berger, D Waldmannstetter, J Lipkova, I Ezhov, G Tetteh, ...
Frontiers in Neuroscience 14, 125, 2020
702020
Shape-aware complementary-task learning for multi-organ segmentation
F Navarro, S Shit, I Ezhov, J Paetzold, A Gafita, JC Peeken, SE Combs, ...
Machine Learning in Medical Imaging: 10th International Workshop, MLMI 2019 …, 2019
66*2019
Red-GAN: Attacking class imbalance via conditioned generation. Yet another medical imaging perspective.
AB Qasim*, I Ezhov*, S Shit, O Schoppe, JC Paetzold, A Sekuboyina, ...
Proceedings of Machine Learning Research 1, 14, 2020
52*2020
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, ...
arXiv preprint arXiv:2103.06205, 2021
36*2021
Verse: a vertebrae labelling and segmentation benchmark
A Sekuboyina, A Bayat, ME Husseini, M Löffler, M Rempfler, J Kukačka, ...
arXiv. org e-Print archive, 2020
342020
ISLES 2022: A multi-center magnetic resonance imaging stroke lesion segmentation dataset
MR Hernandez Petzsche, E de la Rosa, U Hanning, R Wiest, ...
Scientific data 9 (1), 762, 2022
312022
Imbalance-aware self-supervised learning for 3d radiomic representations
H Li, FF Xue, K Chaitanya, S Luo, I Ezhov, B Wiestler, J Zhang, B Menze
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
232021
Neural parameters estimation for brain tumor growth modeling
I Ezhov*, J Lipkova*, S Shit, F Kofler, N Collomb, B Lemasson, E Barbier, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2019
222019
Relationformer: A Unified Framework for Image-to-Graph Generation
S Shit, R Koner, B Wittmann, J Paetzold, I Ezhov, H Li, J Pan, ...
ECCV 2022, 2022
192022
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, ...
Thirty-Fifth Conference on Neural Information Processing Systems Datasets …, 2021
18*2021
Geometry-aware neural solver for fast Bayesian calibration of brain tumor models
I Ezhov, T Mot, S Shit, J Lipkova, JC Paetzold, F Kofler, F Navarro
IEEE Transactions on Medical Imaging, 2021, 2021
17*2021
clDice-a Novel Connectivity-Preserving Loss Function for Vessel Segmentation
JC Paetzold, S Shit, I Ezhov, G Tetteh, A Ertürk, B Menze
Medical Imaging Meets NeurIPS 2019, 2019
12*2019
A distance-based loss for smooth and continuous skin layer segmentation in optoacoustic images
S Gerl, JC Paetzold, H He, I Ezhov, S Shit, F Kofler, A Bayat, G Tetteh, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2020
112020
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
102023
Landmark-free statistical shape modeling via neural flow deformations
D Lüdke, T Amiranashvili, F Ambellan, I Ezhov, BH Menze, S Zachow
International Conference on Medical Image Computing and Computer-Assisted …, 2022
92022
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