Raphael Meier

According to our database1, Raphael Meier authored at least 23 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2024
Synthetic Photography Detection: A Visual Guidance for Identifying Synthetic Images Created by AI.
CoRR, 2024

Sparse vs Contiguous Adversarial Pixel Perturbations in Multimodal Models: An Empirical Analysis.
CoRR, 2024

Synthetic Image Generation in Cyber Influence Operations: An Emergent Threat?
CoRR, 2024

2023
Social Media Influence Operations.
CoRR, 2023

2021
Combining unsupervised and supervised learning for predicting the final stroke lesion.
Medical Image Anal., 2021

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

2020
Uncertainty-Driven Refinement of Tumor-Core Segmentation Using 3D-to-2D Networks with Label Uncertainty.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019
Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks.
CoRR, 2019

Triplanar Ensemble of 3D-to-2D CNNs with Label-Uncertainty for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2018
Enhancing interpretability of automatically extracted machine learning features: application to a RBM-Random Forest system on brain lesion segmentation.
Medical Image Anal., 2018

Uncertainty-driven Sanity Check: Application to Postoperative Brain Tumor Cavity Segmentation.
CoRR, 2018

Enhancing Clinical MRI Perfusion Maps with Data-Driven Maps of Complementary Nature for Lesion Outcome Prediction.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Automatic Brain Tumor Grading from MRI Data Using Convolutional Neural Networks and Quality Assessment.
Proceedings of the Understanding and Interpreting Machine Learning in Medical Image Computing Applications, 2018

Ensembles of Densely-Connected CNNs with Label-Uncertainty for Brain Tumor Segmentation.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

On the Effect of Inter-observer Variability for a Reliable Estimation of Uncertainty of Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018

Synthetic Perfusion Maps: Imaging Perfusion Deficits in DSC-MRI with Deep Learning.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2018

2017
Perturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs.
CoRR, 2017

Towards Uncertainty-Assisted Brain Tumor Segmentation and Survival Prediction.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2017

2016
CRF-Based Brain Tumor Segmentation: Alleviating the Shrinking Bias.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2016

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

Parameter Learning for CRF-Based Tissue Segmentation of Brain Tumors.
Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2015

2014
Patient-Specific Semi-supervised Learning for Postoperative Brain Tumor Segmentation.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2014, 2014

Interactive segmentation of MR images from brain tumor patients.
Proceedings of the IEEE 11th International Symposium on Biomedical Imaging, 2014


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