
Benedikt Wiestler
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2020 – today
- 2020
- [c12]Christoph Baur, Benedikt Wiestler
, Shadi Albarqouni
, Nassir Navab:
Bayesian Skip-Autoencoders for Unsupervised Hyperintense Anomaly Detection in High Resolution Brain Mri. ISBI 2020: 1905-1909 - [c11]Maximilian Möller, Matthias Kohl, Stefan Braunewell, Florian Kofler, Benedikt Wiestler
, Jan S. Kirschke, Björn H. Menze, Marie Piraud:
Reliable Saliency Maps for Weakly-Supervised Localization of Disease Patterns. iMIMIC/MIL3ID/LABELS@MICCAI 2020: 63-72 - [c10]Christoph Baur, Benedikt Wiestler
, Shadi Albarqouni, Nassir Navab:
Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI. MICCAI (4) 2020: 552-561 - [c9]Christoph Baur, Robert Graf, Benedikt Wiestler
, Shadi Albarqouni, Nassir Navab:
SteGANomaly: Inhibiting CycleGAN Steganography for Unsupervised Anomaly Detection in Brain MRI. MICCAI (2) 2020: 718-727 - [c8]Diana Waldmannstetter, Fernando Navarro, Benedikt Wiestler
, Jan S. Kirschke, Anjany Sekuboyina, Ester Molero, Bjoern H. Menze:
Reinforced Redetection of Landmark in Pre- and Post-operative Brain Scan Using Anatomical Guidance for Image Alignment. WBIR 2020: 81-90 - [i9]Hongwei Li, Timo Loehr, Benedikt Wiestler, Jianguo Zhang, Bjoern H. Menze:
e-UDA: Efficient Unsupervised Domain Adaptation for Cross-Site Medical Image Segmentation. CoRR abs/2001.09313 (2020) - [i8]Abhijeet Parida, Aadhithya Sankar, Rami Eisawy, Tom Finck, Benedikt Wiestler, Franz Pfister, Julia Moosbauer:
Train, Learn, Expand, Repeat. CoRR abs/2003.08469 (2020) - [i7]Christoph Baur, Stefan Denner, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab:
Autoencoders for Unsupervised Anomaly Segmentation in Brain MR Images: A Comparative Study. CoRR abs/2004.03271 (2020) - [i6]Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab:
Scale-Space Autoencoders for Unsupervised Anomaly Segmentation in Brain MRI. CoRR abs/2006.12852 (2020) - [i5]Ivan Ezhov, Tudor Mot, Suprosanna Shit, Jana Lipková, Johannes C. Paetzold, Florian Kofler, Fernando Navarro, Marie Metz, Benedikt Wiestler, Björn H. Menze:
Real-time Bayesian personalization via a learnable brain tumor growth model. CoRR abs/2009.04240 (2020)
2010 – 2019
- 2019
- [j2]Jana Lipková
, Panagiotis Angelikopoulos, Stephen Wu, Esther Alberts, Benedikt Wiestler
, Christian Diehl, Christine Preibisch
, Thomas Pyka, Stephanie Combs, Panagiotis E. Hadjidoukas
, Koen Van Leemput
, Petros Koumoutsakos
, John S. Lowengrub, Bjoern H. Menze:
Personalized Radiotherapy Design for Glioblastoma: Integrating Mathematical Tumor Models, Multimodal Scans, and Bayesian Inference. IEEE Trans. Medical Imaging 38(8): 1875-1884 (2019) - [c7]Florian Kofler, Johannes C. Paetzold, Ivan Ezhov, Suprosanna Shit, Daniel Krahulec, Jan S. Kirschke, Claus Zimmer, Benedikt Wiestler
, Bjoern H. Menze:
A Baseline for Predicting Glioblastoma Patient Survival Time with Classical Statistical Models and Primitive Features Ignoring Image Information. BrainLes@MICCAI (1) 2019: 254-261 - [c6]Anees Kazi, Shayan Shekarforoush
, S. Arvind Krishna, Hendrik Burwinkel, Gerome Vivar, Benedikt Wiestler
, Karsten Kortüm, Seyed-Ahmad Ahmadi, Shadi Albarqouni
, Nassir Navab:
Graph Convolution Based Attention Model for Personalized Disease Prediction. MICCAI (4) 2019: 122-130 - [c5]Hongwei Li
, Johannes C. Paetzold, Anjany Sekuboyina, Florian Kofler, Jianguo Zhang, Jan S. Kirschke, Benedikt Wiestler
, Bjoern H. Menze:
DiamondGAN: Unified Multi-modal Generative Adversarial Networks for MRI Sequences Synthesis. MICCAI (4) 2019: 795-803 - [c4]Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab:
Fusing Unsupervised and Supervised Deep Learning for White Matter Lesion Segmentation. MIDL 2019: 63-72 - [i4]Hongwei Li, Johannes C. Paetzold, Anjany Sekuboyina, Florian Kofler, Jianguo Zhang, Jan S. Kirschke, Benedikt Wiestler, Bjoern H. Menze:
DiamondGAN: Unified Multi-Modal Generative Adversarial Networks for MRI Sequences Synthesis. CoRR abs/1904.12894 (2019) - 2018
- [c3]Miguel Molina-Romero
, Benedikt Wiestler
, Pedro A. Gómez
, Marion I. Menzel
, Bjoern H. Menze
:
Deep Learning with Synthetic Diffusion MRI Data for Free-Water Elimination in Glioblastoma Cases. MICCAI (3) 2018: 98-106 - [c2]Christoph Baur, Benedikt Wiestler
, Shadi Albarqouni
, Nassir Navab:
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images. BrainLes@MICCAI (1) 2018: 161-169 - [i3]Christoph Baur, Benedikt Wiestler, Shadi Albarqouni, Nassir Navab:
Deep Autoencoding Models for Unsupervised Anomaly Segmentation in Brain MR Images. CoRR abs/1804.04488 (2018) - [i2]Jana Lipková, Panagiotis Angelikopoulos, Stephen Wu, Esther Alberts, Benedikt Wiestler, Christian Diehl, Christine Preibisch, Thomas Pyka, Stephanie Combs, Panagiotis E. Hadjidoukas, Koen Van Leemput, Petros Koumoutsakos, John S. Lowengrub, Bjoern H. Menze:
Personalized Radiotherapy Planning for Glioma Using Multimodal Bayesian Model Calibration. CoRR abs/1807.00499 (2018) - [i1]Spyridon Bakas, Mauricio Reyes, András Jakab, Stefan Bauer, Markus Rempfler, Alessandro Crimi, Russell Takeshi Shinohara, Christoph Berger, Sung Min Ha, Martin Rozycki, Marcel Prastawa, Esther Alberts, Jana Lipková, John B. Freymann, Justin S. Kirby, Michel Bilello, Hassan M. Fathallah-Shaykh, Roland Wiest, Jan Kirschke, Benedikt Wiestler, Rivka R. Colen, Aikaterini Kotrotsou, Pamela LaMontagne, Daniel S. Marcus, Mikhail Milchenko, Arash Nazeri, Marc-André Weber, Abhishek Mahajan, Ujjwal Baid, Dongjin Kwon, Manu Agarwal, Mahbubul Alam, Alberto Albiol, Antonio Albiol, Alex Varghese, Tran Anh Tuan, Tal Arbel, Aaron Avery, Pranjal B., Subhashis Banerjee, Thomas Batchelder, Kayhan N. Batmanghelich, Enzo Battistella, Martin Bendszus, Eze Benson, José Bernal, George Biros, Mariano Cabezas, Siddhartha Chandra, Yi-Ju Chang, et al.:
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge. CoRR abs/1811.02629 (2018) - 2017
- [c1]Esther Alberts, Giles Tetteh, Stefano Trebeschi, Marie Bieth, Alexander Valentinitsch, Benedikt Wiestler
, Claus Zimmer, Bjoern H. Menze
:
Multi-modal Image Classification Using Low-Dimensional Texture Features for Genomic Brain Tumor Recognition. GRAIL/MFCA/MICGen@MICCAI 2017: 201-209 - 2015
- [j1]Moritz Zaiss, Johannes Windschuh, Daniel Paech
, Jan-Eric Meissner, Sina Burth, Benjamin Schmitt, Philip Kickingereder
, Benedikt Wiestler
, Wolfgang Wick, Martin Bendszus, Heinz-Peter Schlemmer, Mark E. Ladd, Peter Bachert, Alexander Radbruch:
Relaxation-compensated CEST-MRI of the human brain at 7 T: Unbiased insight into NOE and amide signal changes in human glioblastoma. NeuroImage 112: 180-188 (2015)
Coauthor Index

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