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Jens Petersen
Jens Petersen
Qualcomm AI Research
Verified email at qti.qualcomm.com - Homepage
Title
Cited by
Cited by
Year
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
5937*2021
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
12712023
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
4032019
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
1862021
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
1712019
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
1542018
Metrics reloaded: recommendations for image analysis validation
L Maier-Hein, A Reinke, P Godau, MD Tizabi, F Buettner, E Christodoulou, ...
Nature methods 21 (2), 195-212, 2024
1512024
Mednext: transformer-driven scaling of convnets for medical image segmentation
S Roy, G Koehler, C Ulrich, M Baumgartner, J Petersen, F Isensee, ...
International Conference on Medical Image Computing and Computer-Assisted …, 2023
1322023
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
882021
Understanding metric-related pitfalls in image analysis validation
A Reinke, MD Tizabi, M Baumgartner, M Eisenmann, D Heckmann-Nötzel, ...
Nature methods 21 (2), 182-194, 2024
762024
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
432022
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
382019
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
322020
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
252018
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
232016
Telestration with augmented reality for visual presentation of intraoperative target structures in minimally invasive surgery: a randomized controlled study
C Wild, F Lang, AS Gerhäuser, MW Schmidt, KF Kowalewski, J Petersen, ...
Surgical Endoscopy 36 (10), 7453-7461, 2022
212022
A residual diffusion model for high perceptual quality codec augmentation
NF Ghouse, J Petersen, A Wiggers, T Xu, G Sautiere
arXiv preprint arXiv:2301.05489, 2023
19*2023
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
192021
Metrics reloaded: a new recommendation framework for biomedical image analysis validation
A Reinke, H Müller
Proceedings of the Medical Imaging with Deep Learning (MIDL 2022), 2022
162022
Telestration with augmented reality improves surgical performance through gaze guidance
EA Felinska, TE Fuchs, A Kogkas, ZW Chen, B Otto, KF Kowalewski, ...
Surgical Endoscopy 37 (5), 3557-3566, 2023
152023
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