activity
20182020
most citedStandardized Assessment of Automatic Segmentation of White Matter Hyperintensities and Results of the WMH Segmentation Challenge

309 citations · 324 across the 5 of their papers we have counts for

collaborators

8 papers

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…

cs.LG20199 cited

ModelHub.AI: Dissemination Platform for Deep Learning Models

Ahmed Hosny, Michael Schwier, Christoph Berger +13

Recent advances in artificial intelligence research have led to a profusion of studies that apply deep learning to problems in image analysis and natural language processing among…

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.CV2019

Automatic detection of lesion load change in Multiple Sclerosis using convolutional neural networks with segmentation confidence

Richard McKinley, Lorenz Grunder, Rik Wepfer +12

The detection of new or enlarged white-matter lesions in multiple sclerosis is a vital task in the monitoring of patients undergoing disease-modifying treatment for multiple sclero…

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…