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Fabian Isensee
Fabian Isensee
HIP Applied Computer Vision Lab, Division of Medical Image Computing, German Cancer Research Center
Verified email at dkfz-heidelberg.de
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
3342*2021
The image biomarker standardization initiative: standardized quantitative radiomics for high-throughput image-based phenotyping
A Zwanenburg, M Vallières, MA Abdalah, HJWL Aerts, V Andrearczyk, ...
Radiology 295 (2), 328-338, 2020
22882020
Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge
S Bakas, M Reyes, A Jakab, S Bauer, M Rempfler, A Crimi, RT Shinohara, ...
arXiv preprint arXiv:1811.02629, 2018
17412018
Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?
O Bernard, A Lalande, C Zotti, F Cervenansky, X Yang, PA Heng, I Cetin, ...
IEEE transactions on medical imaging 37 (11), 2514-2525, 2018
13862018
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
9112023
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
8322018
Brain tumor segmentation and radiomics survival prediction: Contribution to the brats 2017 challenge
F Isensee, P Kickingereder, W Wick, M Bendszus, KH Maier-Hein
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2018
6262018
The medical segmentation decathlon
M Antonelli, A Reinke, S Bakas, K Farahani, A Kopp-Schneider, ...
Nature communications 13 (1), 4128, 2022
6152022
No new-net
F Isensee, P Kickingereder, W Wick, M Bendszus, KH Maier-Hein
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2019
5202019
CHAOS challenge-combined (CT-MR) healthy abdominal organ segmentation
AE Kavur, NS Gezer, M Barış, S Aslan, PH Conze, V Groza, DD Pham, ...
Medical Image Analysis 69, 101950, 2021
4462021
The state of the art in kidney and kidney tumor segmentation in contrast-enhanced CT imaging: Results of the KiTS19 challenge
N Heller, F Isensee, KH Maier-Hein, X Hou, C Xie, F Li, Y Nan, G Mu, ...
Medical image analysis 67, 101821, 2021
4412021
Automated brain extraction of multisequence MRI using artificial neural networks
F Isensee, M Schell, I Pflueger, G Brugnara, D Bonekamp, U Neuberger, ...
Human brain mapping 40 (17), 4952-4964, 2019
3972019
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
3462019
Automatic cardiac disease assessment on cine-MRI via time-series segmentation and domain specific features
F Isensee, PF Jaeger, PM Full, I Wolf, S Engelhardt, KH Maier-Hein
Statistical Atlases and Computational Models of the Heart. ACDC and MMWHS …, 2018
3302018
nnU-Net for brain tumor segmentation
F Isensee, PF Jäger, PM Full, P Vollmuth, KH Maier-Hein
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries …, 2021
2712021
Retina U-Net: Embarrassingly simple exploitation of segmentation supervision for medical object detection
PF Jaeger, SAA Kohl, S Bickelhaupt, F Isensee, TA Kuder, HP Schlemmer, ...
Machine Learning for Health Workshop, 171-183, 2020
2192020
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
1412019
International MICCAI Brainlesion Workshop
F Isensee, P Kickingereder, W Wick, M Bendszus, KH Maier-Hein
Cham: Springer, 287-297, 2017
1412017
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
1392021
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
1392018
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