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ORCIDRaphael Meier
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2020 – today
- 2024
[i14]Melanie Mathys, Marco Willi
, Michael Graber, Raphael Meier:
Synthetic Image Generation in Cyber Influence Operations: An Emergent Threat? CoRR abs/2403.12207 (2024)- [i13]Cristian-Alexandru Botocan, Raphael Meier, Ljiljana Dolamic:
Sparse vs Contiguous Adversarial Pixel Perturbations in Multimodal Models: An Empirical Analysis. CoRR abs/2407.18251 (2024) - [i12]Melanie Mathys, Marco Willi, Raphael Meier:
Synthetic Photography Detection: A Visual Guidance for Identifying Synthetic Images Created by AI. CoRR abs/2408.06398 (2024) - 2023
- [i11]Raphael Meier:
Social Media Influence Operations. CoRR abs/2309.03670 (2023) - 2021
- [j3]Adriano Pinto, Sérgio Pereira, Raphael Meier, Roland Wiest, Victor Alves, Mauricio Reyes, Carlos A. Silva:
Combining unsupervised and supervised learning for predicting the final stroke lesion. Medical Image Anal. 69: 101888 (2021) - [i10]Adriano Pinto, Sérgio Pereira, Raphael Meier, Roland Wiest, Victor Alves, Mauricio Reyes, Carlos A. Silva:
Combining unsupervised and supervised learning for predicting the final stroke lesion. CoRR abs/2101.00489 (2021) - [i9]Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil S. Nalawade, Chandan Ganesh, Benjamin C. Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Alexandra Daza, Catalina Gómez Caballero, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Linmin Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Verónica Vilaplana, Hugh McHugh, Gonzalo D. Maso Talou, Alan Wang, Jay B. Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Thumbavanam Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicolas Boutry, Alexis Huard, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Élodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Lladó, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas J. Tustison, Craig H. Meyer, Nisarg A. Shah, Sanjay N. Talbar, Marc-André Weber, Abhishek Mahajan, András Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko, Daniel S. Marcus, Aikaterini Kotrotsou, Rivka Colen, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Bjoern H. Menze, Spyridon Bakas, Yarin Gal, Tal Arbel:
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. CoRR abs/2112.10074 (2021) - 2020
- [c12]Richard McKinley, Michael Rebsamen, Katrin Daetwyler, Raphael Meier, Piotr Radojewski, Roland Wiest:
Uncertainty-Driven Refinement of Tumor-Core Segmentation Using 3D-to-2D Networks with Label Uncertainty. BrainLes@MICCAI (1) 2020: 401-411 - [i8]Richard McKinley, Michael Rebsamen, Katrin Daetwyler, Raphael Meier, Piotr Radojewski, Roland Wiest:
Uncertainty-driven refinement of tumor-core segmentation using 3D-to-2D networks with label uncertainty. CoRR abs/2012.06436 (2020)
2010 – 2019
- 2019
- [c11]Richard McKinley, Michael Rebsamen, Raphael Meier, Roland Wiest:
Triplanar Ensemble of 3D-to-2D CNNs with Label-Uncertainty for Brain Tumor Segmentation. BrainLes@MICCAI (1) 2019: 379-387 - [i7]Richard McKinley, Michael Rebsamen, Raphael Meier, Mauricio Reyes, Christian Rummel, Roland Wiest:
Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks. CoRR abs/1904.02436 (2019) - 2018
- [j2]Sérgio Pereira, Raphael Meier, Richard McKinley, Roland Wiest, Victor Alves, Carlos A. Silva, Mauricio Reyes:
Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation. Medical Image Anal. 44: 228-244 (2018) - [c10]Sérgio Pereira, Raphael Meier, Victor Alves, Mauricio Reyes, Carlos A. Silva:
Automatic Brain Tumor Grading from MRI Data Using Convolutional Neural Networks and Quality Assessment. MLCN/DLF/iMIMIC@MICCAI 2018: 106-114 - [c9]Adriano Pinto, Sérgio Pereira, Raphael Meier, Victor Alves, Roland Wiest, Carlos A. Silva, Mauricio Reyes:
Enhancing Clinical MRI Perfusion Maps with Data-Driven Maps of Complementary Nature for Lesion Outcome Prediction. MICCAI (3) 2018: 107-115 - [c8]Andreas Hess, Raphael Meier, Johannes Kaesmacher, Simon Jung, Fabien Scalzo, David S. Liebeskind, Roland Wiest, Richard McKinley:
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning. BrainLes@MICCAI (1) 2018: 447-455 - [c7]Richard McKinley, Raphael Meier, Roland Wiest:
Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation. BrainLes@MICCAI (2) 2018: 456-465 - [c6]Alain Jungo, Raphael Meier, Ekin Ermis, Marcela Blatti-Moreno, Evelyn Herrmann, Roland Wiest, Mauricio Reyes:
On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation. MICCAI (1) 2018: 682-690 - [e1]Danail Stoyanov, Zeike Taylor, Seyed Mostafa Kia, Ipek Oguz, Mauricio Reyes, Anne L. Martel, Lena Maier-Hein, Andre F. Marquand, Edouard Duchesnay, Tommy Löfstedt, Bennett A. Landman, M. Jorge Cardoso, Carlos A. Silva, Sérgio Pereira, Raphael Meier:
Understanding and Interpreting Machine Learning in Medical Image Computing Applications - First International Workshops MLCN 2018, DLF 2018, and iMIMIC 2018, Held in Conjunction with MICCAI 2018, Granada, Spain, September 16-20, 2018, Proceedings. Lecture Notes in Computer Science 11038, Springer 2018, ISBN 978-3-030-02627-1 [contents] - [i6]Alain Jungo, Raphael Meier, Ekin Ermis, Marcela Blatti-Moreno, Evelyn Herrmann, Roland Wiest, Mauricio Reyes:
On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation. CoRR abs/1806.02562 (2018) - [i5]Alain Jungo, Raphael Meier, Ekin Ermis, Evelyn Herrmann, Mauricio Reyes:
Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation. CoRR abs/1806.03106 (2018) - [i4]Andreas Hess, Raphael Meier, Johannes Kaesmacher, Simon Jung, Fabien Scalzo, David S. Liebeskind, Roland Wiest, Richard McKinley:
Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning. CoRR abs/1806.03848 (2018) - [i3]Adriano Pinto, Sérgio Pereira, Raphael Meier, Victor Alves, Roland Wiest, Carlos A. Silva, Mauricio Reyes:
Enhancing clinical MRI Perfusion maps with data-driven maps of complementary nature for lesion outcome prediction. CoRR abs/1806.04413 (2018) - [i2]Sérgio Pereira, Raphael Meier, Victor Alves, Mauricio Reyes, Carlos A. Silva:
Automatic brain tumor grading from MRI data using convolutional neural networks and quality assessment. CoRR abs/1809.09468 (2018) - 2017
- [c5]Alain Jungo, Richard McKinley, Raphael Meier, Urspeter Knecht, Luis Vera, Julián Pérez-Beteta, David Molina-García, Víctor M. Pérez-García, Roland Wiest, Mauricio Reyes:
Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction. BrainLes@MICCAI 2017: 474-485 - [i1]Raphael Meier, Urspeter Knecht, Alain Jungo, Roland Wiest, Mauricio Reyes:
Perturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs. CoRR abs/1703.00312 (2017) - 2016
- [c4]Raphael Meier, Urspeter Knecht, Roland Wiest, Mauricio Reyes:
CRF-Based Brain Tumor Segmentation: Alleviating the Shrinking Bias. BrainLes@MICCAI 2016: 100-107 - 2015
- [j1]Bjoern H. Menze, András Jakab, Stefan Bauer, Jayashree Kalpathy-Cramer, Keyvan Farahani, Justin S. Kirby, Yuliya Burren, Nicole Porz, Johannes Slotboom, Roland Wiest, Levente Lanczi, Elizabeth R. Gerstner, Marc-André Weber, Tal Arbel, Brian B. Avants, Nicholas Ayache, Patricia Buendia, D. Louis Collins, Nicolas Cordier, Jason J. Corso, Antonio Criminisi, Tilak Das, Herve Delingette, Çagatay Demiralp, Christopher R. Durst, Michel Dojat, Senan Doyle, Joana Festa, Florence Forbes, Ezequiel Geremia, Ben Glocker, Polina Golland, Xiaotao Guo, Andac Hamamci, Khan M. Iftekharuddin, Raj Jena, Nigel M. John, Ender Konukoglu, Danial Lashkari, José Antonio Mariz, Raphael Meier, Sérgio Pereira, Doina Precup, Stephen J. Price, Tammy Riklin Raviv, Syed M. S. Reza, Michael T. Ryan, Duygu Sarikaya, Lawrence H. Schwartz, Hoo-Chang Shin, Jamie Shotton, Carlos A. Silva, Nuno J. Sousa, Nagesh K. Subbanna, Gábor Székely, Thomas J. Taylor, Owen M. Thomas, Nicholas J. Tustison, Gözde B. Ünal, Flor Vasseur, Max Wintermark, Dong Hye Ye, Liang Zhao, Binsheng Zhao, Darko Zikic, Marcel Prastawa, Mauricio Reyes, Koen Van Leemput:
The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). IEEE Trans. Medical Imaging 34(10): 1993-2024 (2015) - [c3]Raphael Meier, Venetia Karamitsou, Simon Habegger, Roland Wiest, Mauricio Reyes:
Parameter Learning for CRF-Based Tissue Segmentation of Brain Tumors. Brainles@MICCAI 2015: 156-167 - 2014
- [c2]Stefan Bauer, Nicole Porz, Raphael Meier, Alessia Pica, Johannes Slotboom, Roland Wiest, Mauricio Reyes:
Interactive segmentation of MR images from brain tumor patients. ISBI 2014: 862-865 - [c1]Raphael Meier, Stefan Bauer, Johannes Slotboom, Roland Wiest, Mauricio Reyes:
Patient-Specific Semi-supervised Learning for Postoperative Brain Tumor Segmentation. MICCAI (1) 2014: 714-721
Coauthor Index
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