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David Zimmerer
David Zimmerer
在 dkfz.de 的电子邮件经过验证
标题
引用次数
引用次数
年份
nnu-net: Self-adapting framework for u-net-based medical image segmentation
F Isensee, J Petersen, A Klein, D Zimmerer, PF Jaeger, S Kohl, ...
arXiv preprint arXiv:1809.10486, 2018
9582018
Unsupervised anomaly localization using variational auto-encoders
D Zimmerer, F Isensee, J Petersen, S Kohl, K Maier-Hein
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
1592019
Exploiting the potential of unlabeled endoscopic video data with self-supervised learning
T Ross, D Zimmerer, A Vemuri, F Isensee, M Wiesenfarth, S Bodenstedt, ...
International journal of computer assisted radiology and surgery 13, 925-933, 2018
1492018
Context-encoding Variational Autoencoder for Unsupervised Anomaly Detection--Short Paper
D Zimmerer, S Kohl, J Petersen, F Isensee, K Maier-Hein
Medical Imaging with Deep Learning (MIDL) 2019, arXiv: 1907.12258, 2019
146*2019
The federated tumor segmentation (fets) challenge
S Pati, U Baid, M Zenk, B Edwards, M Sheller, GA Reina, P Foley, ...
arXiv preprint arXiv:2105.05874, 2021
842021
Sam. md: Zero-shot medical image segmentation capabilities of the segment anything model
S Roy, T Wald, G Koehler, MR Rokuss, N Disch, J Holzschuh, D Zimmerer, ...
arXiv preprint arXiv:2304.05396, 2023
762023
batchgenerators—a python framework for data augmentation
F Isensee, P Jäger, J Wasserthal, D Zimmerer, J Petersen, S Kohl, ...
Zenodo 3632567, 2020
58*2020
Mood 2020: A public benchmark for out-of-distribution detection and localization on medical images
D Zimmerer, PM Full, F Isensee, P Jäger, T Adler, J Petersen, G Köhler, ...
IEEE Transactions on Medical Imaging 41 (10), 2728-2738, 2022
352022
Biomedical image analysis competitions: The state of current participation practice
M Eisenmann, A Reinke, V Weru, MD Tizabi, F Isensee, TJ Adler, ...
arXiv preprint arXiv:2212.08568, 2022
252022
A Case for the Score: Identifying Image Anomalies using Variational Autoencoder Gradients
D Zimmerer, J Petersen, SAA Kohl, KH Maier-Hein
Medical Imaging meets NeurIPS Workshop 2018, 2018
252018
Sam. md: Zero-shot medical image segmentation capabilities of the segment anything model
T Wald, S Roy, G Koehler, N Disch, MR Rokuss, J Holzschuh, D Zimmerer, ...
Medical Imaging with Deep Learning, short paper track, 2023
182023
Why is the winner the best?
M Eisenmann, A Reinke, V Weru, MD Tizabi, F Isensee, TJ Adler, S Ali, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
172023
Medical out-of-distribution analysis challenge (Mar 2020)
D Zimmerer, J Petersen, G Köhler, P Jäger, P Full, T Roß, T Adler, ...
URL https://doi. org/10.5281/zenodo 3784230, 0
16*
Spiking convolutional deep belief networks
J Kaiser, D Zimmerer, JCV Tieck, S Ulbrich, A Roennau, R Dillmann
Artificial Neural Networks and Machine Learning–ICANN 2017: 26th …, 2017
142017
Robust environment perception for the audi autonomous driving cup
F Kuhnt, M Pfeiffer, P Zimmer, D Zimmerer, JM Gomer, V Kaiser, ...
2016 IEEE 19th International Conference on Intelligent Transportation …, 2016
102016
Continuous-time deep glioma growth models
J Petersen, F Isensee, G Köhler, PF Jäger, D Zimmerer, U Neuberger, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2021: 24th …, 2021
92021
GP-ConvCNP: Better generalization for conditional convolutional Neural Processes on time series data
J Petersen, G Köhler, D Zimmerer, F Isensee, PF Jäger, KH Maier-Hein
Uncertainty in Artificial Intelligence, 939-949, 2021
7*2021
High-and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection
D Zimmerer, J Petersen, K Maier-Hein
Medical Imaging meets NeurIPS Workshop 2019, 2019
72019
Cradl: Contrastive representations for unsupervised anomaly detection and localization
CT Lüth, D Zimmerer, G Koehler, PF Jaeger, F Isensee, J Petersen, ...
arXiv preprint arXiv:2301.02126, 2023
52023
Leveraging foundation models for content-based medical image retrieval in radiology
S Denner, D Zimmerer, D Bounias, M Bujotzek, S Xiao, L Kausch, ...
arXiv preprint arXiv:2403.06567, 2024
22024
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