activity
20172021
most citedStandardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge

309 citations · 454 across the 6 of their papers we have counts for

collaborators

13 papers

cs.CV202189 cited

The RSNA-ASNR-MICCAI BraTS 2021 Benchmark on Brain Tumor Segmentation and Radiogenomic Classification

Ujjwal Baid, Satyam Ghodasara, Suyash Mohan +100

The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), the American Society of Neuroradiology (ASNR)…

eess.IV202147 cited

Combining unsupervised and supervised learning for predicting the final stroke lesion

Adriano Pinto, Sérgio Pereira, Raphael Meier +4

Predicting the final ischaemic stroke lesion provides crucial information regarding the volume of salvageable hypoperfused tissue, which helps physicians in the difficult decision-…

eess.IV2020

Uncertainty-driven refinement of tumor-core segmentation using 3D-to-2D networks with label uncertainty

Richard McKinley, Micheal Rebsamen, Katrin Daetwyler +3

The BraTS dataset contains a mixture of high-grade and low-grade gliomas, which have a rather different appearance: previous studies have shown that performance can be improved by…

eess.IV2019

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…

cs.LG20196 cited

Few-shot brain segmentation from weakly labeled data with deep heteroscedastic multi-task networks

Richard McKinley, Michael Rebsamen, Raphael Meier +3

In applications of supervised learning applied to medical image segmentation, the need for large amounts of labeled data typically goes unquestioned. In particular, in the case of…

cs.CV2019309 cited

Standardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge

Hugo J. Kuijf, J. Matthijs Biesbroek, Jeroen de Bresser +41

Quantification of cerebral white matter hyperintensities (WMH) of presumed vascular origin is of key importance in many neurological research studies. Currently, measurements are o…