3 citations · 4 across the 3 of their papers we have counts for
3 papers
Stratify or Inject: Two Simple Training Strategies to Improve Brain Tumor Segmentation
Raphael Meier, Michael Rebsamen, Urspeter Knecht +3
Deep learning methods for brain tumor segmentation are typically trained in an ad hoc fashion on all available data. Brain tumors are tremendously heterogeneous in image appearance…
Deep Learning versus Classical Regression for Brain Tumor Patient Survival Prediction
Yannick Suter, Alain Jungo, Michael Rebsamen +4
Deep learning for regression tasks on medical imaging data has shown promising results. However, compared to other approaches, their power is strongly linked to the dataset size. I…
Perturb-and-MPM: Quantifying Segmentation Uncertainty in Dense Multi-Label CRFs
Raphael Meier, Urspeter Knecht, Alain Jungo +2
This paper proposes a novel approach for uncertainty quantification in dense Conditional Random Fields (CRFs). The presented approach, called Perturb-and-MPM, enables efficient, ap…