Interactive segmentation of MR images from brain tumor patients. - Stefan Bauer; Nicole Porz; Raphael Meier; Alessia Pica; Johannes Slotboom; Roland Wiest; Mauricio Reyes 001 (ISBI, 2014)

Patient-Specific Semi-supervised Learning for Postoperative Brain Tumor Segmentation. - Raphael Meier; Stefan Bauer; Johannes Slotboom; Roland Wiest; Mauricio Reyes 001 (MICCAI (1), 2014)

Parameter Learning for CRF-Based Tissue Segmentation of Brain Tumors. - Raphael Meier; Venetia Karamitsou; Simon Habegger; Roland Wiest; Mauricio Reyes 001 (Brainles@MICCAI, 2015)

The Multimodal Brain Tumor Image Segmentation Benchmark (BRATS). - 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; et al. (IEEE Trans. Medical Imaging, 2015)

CRF-Based Brain Tumor Segmentation: Alleviating the Shrinking Bias. - Raphael Meier; Urspeter Knecht; Roland Wiest; Mauricio Reyes 001 (BrainLes@MICCAI, 2016)

Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction. - Alain Jungo; Richard McKinley; Raphael Meier; Urspeter Knecht; Luis Vera; Julián Pérez-Beteta; David Molina-García; Víctor M. Pérez-García; Roland Wiest; Mauricio Reyes 001 (BrainLes@MICCAI, 2017)

Perturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs. - Raphael Meier; Urspeter Knecht; Alain Jungo; Roland Wiest; Mauricio Reyes 001 (CoRR, 2017)

Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning. - Andreas Hess 005; Raphael Meier; Johannes Kaesmacher; Simon Jung; Fabien Scalzo; David S. Liebeskind; Roland Wiest; Richard McKinley (BrainLes@MICCAI (1), 2018)

On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation. - Alain Jungo; Raphael Meier; Ekin Ermis; Marcela Blatti-Moreno; Evelyn Herrmann; Roland Wiest; Mauricio Reyes 001 (MICCAI (1), 2018)

Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation. - Richard McKinley; Raphael Meier; Roland Wiest (BrainLes@MICCAI (2), 2018)

Automatic Brain Tumor Grading from MRI Data Using Convolutional Neural Networks and Quality Assessment. - Sérgio Pereira; Raphael Meier; Victor Alves; Mauricio Reyes 001; Carlos A. Silva 002 (MLCN/DLF/iMIMIC@MICCAI, 2018)

Enhancing Clinical MRI Perfusion Maps with Data-Driven Maps of Complementary Nature for Lesion Outcome Prediction. - Adriano Pinto; Sérgio Pereira; Raphael Meier; Victor Alves; Roland Wiest; Carlos A. Silva 002; Mauricio Reyes 001 (MICCAI (3), 2018)

Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation. - Alain Jungo; Raphael Meier; Ekin Ermis; Evelyn Herrmann; Mauricio Reyes 001 (CoRR, 2018)

Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation. - Sérgio Pereira; Raphael Meier; Richard McKinley; Roland Wiest; Victor Alves; Carlos A. Silva 002; Mauricio Reyes 001 (Medical Image Anal., 2018)

Triplanar Ensemble of 3D-to-2D CNNs with Label-Uncertainty for Brain Tumor Segmentation. - Richard McKinley; Michael Rebsamen; Raphael Meier; Roland Wiest (BrainLes@MICCAI (1), 2019)

Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks. - Richard McKinley; Michael Rebsamen; Raphael Meier; Mauricio Reyes 001; Christian Rummel; Roland Wiest (CoRR, 2019)

Uncertainty-Driven Refinement of Tumor-Core Segmentation Using 3D-to-2D Networks with Label Uncertainty. - Richard McKinley; Michael Rebsamen; Katrin Daetwyler; Raphael Meier; Piotr Radojewski; Roland Wiest (BrainLes@MICCAI (1), 2020)

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. - 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; et al. (CoRR, 2021)

Combining unsupervised and supervised learning for predicting the final stroke lesion. - Adriano Pinto; Sérgio Pereira; Raphael Meier; Roland Wiest; Victor Alves; Mauricio Reyes 001; Carlos A. Silva 002 (Medical Image Anal., 2021)

Social Media Influence Operations. - Raphael Meier (CoRR, 2023)

Synthetic Image Generation in Cyber Influence Operations: An Emergent Threat? - Melanie Mathys; Marco Willi; Michael Graber; Raphael Meier (CoRR, 2024)

Sparse vs Contiguous Adversarial Pixel Perturbations in Multimodal Models: An Empirical Analysis. - Cristian-Alexandru Botocan; Raphael Meier; Ljiljana Dolamic (CoRR, 2024)

Synthetic Photography Detection: A Visual Guidance for Identifying Synthetic Images Created by AI. - Melanie Mathys; Marco Willi; Raphael Meier (CoRR, 2024)

Threats and Opportunities in AI-generated Images for Armed Forces. - Raphael Meier (CoRR, 2025)

A Manually Annotated Image-Caption Dataset for Detecting Children in the Wild. - Klim Kireev; Ana-Maria Cretu 002; Raphael Meier; Sarah Adel Bargal; Elissa M. Redmiles; Carmela Troncoso (CoRR, 2025)