Fabian Isensee
Fabian Isensee
Division of Medical Image Computing, German Cancer Research Center
在 dkfz-heidelberg.de 的电子邮件经过验证
标题
引用次数
引用次数
年份
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
4012018
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
3492020
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
3012018
Brain tumor segmentation and radiomics survival prediction: Contribution to the brats 2017 challenge
F Isensee, P Kickingereder, W Wick, M Bendszus, KH Maier-Hein
International MICCAI Brainlesion Workshop, 287-297, 2017
2322017
No new-net
F Isensee, P Kickingereder, W Wick, M Bendszus, KH Maier-Hein
International MICCAI Brainlesion Workshop, 234-244, 2018
1752018
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
1692018
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
International workshop on statistical atlases and computational models of …, 2017
1222017
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, 1-9, 2020
114*2020
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
772019
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
492020
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 (6), 925-933, 2018
462018
Reconstruction of initial pressure from limited view photoacoustic images using deep learning
D Waibel, J Gröhl, F Isensee, T Kirchner, K Maier-Hein, L Maier-Hein
Photons Plus Ultrasound: Imaging and Sensing 2018 10494, 104942S, 2018
392018
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
272019
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
272018
An attempt at beating the 3D U-Net
F Isensee, KH Maier-Hein
arXiv preprint arXiv:1908.02182, 2019
212019
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, 2020
202020
Brain tumor segmentation using large receptive field deep convolutional neural networks
F Isensee, P Kickingereder, D Bonekamp, M Bendszus, W Wick, ...
Bildverarbeitung für die Medizin 2017, 86-91, 2017
202017
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, 101950, 2020
182020
Can virtual contrast enhancement in brain MRI replace gadolinium?: a feasibility study
J Kleesiek, JN Morshuis, F Isensee, K Deike-Hofmann, D Paech, ...
Investigative radiology 54 (10), 653-660, 2019
182019
Unsupervised anomaly localization using variational auto-encoders
D Zimmerer, F Isensee, J Petersen, S Kohl, K Maier-Hein
International Conference on Medical Image Computing and Computer-Assisted …, 2019
142019
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