Jens Petersen
Jens Petersen
Qualcomm AI Research
Verified email at - Homepage
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nnU-Net: a self-configuring method for deep learning-based biomedical image segmentation
F Isensee, PF Jaeger, SAA Kohl, J Petersen, KH Maier-Hein
Nature methods 18 (2), 203-211, 2021
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
Automated quantitative tumour response assessment of MRI in neuro-oncology with artificial neural networks: a multicentre, retrospective study
P Kickingereder, F Isensee, I Tursunova, J Petersen, U Neuberger, ...
The Lancet Oncology 20 (5), 728-740, 2019
Automated design of deep learning methods for biomedical image segmentation
F Isensee, PF Jäger, SAA Kohl, J Petersen, KH Maier-Hein
arXiv preprint arXiv:1904.08128, 2019
nnU-Net: Breaking the Spell on Successful Medical Image Segmentation
F Isensee, J Petersen, SAA Kohl, PF Jäger, KH Maier-Hein
arXiv preprint arXiv:1904.08128, 2019
Context-encoding variational autoencoder for unsupervised anomaly detection
D Zimmerer, SAA Kohl, J Petersen, F Isensee, KH Maier-Hein
arXiv preprint arXiv:1812.05941, 2018
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
Common limitations of image processing metrics: A picture story
A Reinke, MD Tizabi, CH Sudre, M Eisenmann, T Rädsch, M Baumgartner, ...
arXiv preprint arXiv:2104.05642, 2021
Deep probabilistic modeling of glioma growth
J Petersen, PF Jäger, F Isensee, SAA Kohl, U Neuberger, W Wick, ...
Medical Image Computing and Computer Assisted Intervention–MICCAI 2019: 22nd …, 2019
Deep-learning-based synthesis of post-contrast T1-weighted MRI for tumour response assessment in neuro-oncology: a multicentre, retrospective cohort study
CJ Preetha, H Meredig, G Brugnara, MA Mahmutoglu, M Foltyn, F Isensee, ...
The Lancet Digital Health 3 (12), e784-e794, 2021
Virtual raters for reproducible and objective assessments in radiology
J Kleesiek, J Petersen, M Döring, K Maier-Hein, U Köthe, W Wick, ...
Scientific reports 6 (1), 25007, 2016
Automated volumetric assessment with artificial neural networks might enable a more accurate assessment of disease burden in patients with multiple sclerosis
G Brugnara, F Isensee, U Neuberger, D Bonekamp, J Petersen, R Diem, ...
European Radiology 30, 2356-2364, 2020
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 2018, 2018
Common limitations of performance metrics in biomedical image analysis
A Reinke, L Maier-Hein, H Müller
Proceedings of the Medical Imaging with Deep Learning (MIDL 2021), 2021
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
High-and Low-level image component decomposition using VAEs for improved reconstruction and anomaly detection
D Zimmerer, J Petersen, K Maier-Hein
arXiv preprint arXiv:1911.12161, 2019
A software application for interactive medical image segmentation with active user guidance
J Petersen, M Bendszus, J Debus, S Heiland, KH Maier-Hein
Proc. MICCAI-IMIC, 70-77, 2016
Automated Containerized Medical Image Processing Based on MITK and Python: A Modular System to Implement Medical Image Processing Pipelines and Visualize Meta Data
CJ Goch, J Metzger, M Hettich, A Klein, T Norajitra, M Götz, J Petersen, ...
Bildverarbeitung für die Medizin 2018: Algorithmen-Systeme-Anwendungen …, 2018
Effective user guidance in online interactive semantic segmentation
J Petersen, M Bendszus, J Debus, S Heiland, KH Maier-Hein
Medical Imaging 2017: Computer-Aided Diagnosis 10134, 486-493, 2017
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
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