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20182025
most citedFederated Learning Enables Big Data for Rare Cancer Boundary Detection

390 citations · 826 across the 15 of their papers we have counts for

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Showing 2019Show all

6 papers · 1 filter

cs.LG2019★ 9 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.LG2019★ 6 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.CV2019★ 309 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…

cs.CV2019★ 12 cited

Simultaneous lesion and neuroanatomy segmentation in Multiple Sclerosis using deep neural networks

Richard McKinley, Rik Wepfer, Fabian Aschwanden +10

Segmentation of white matter lesions and deep grey matter structures is an important task in the quantification of magnetic resonance imaging in multiple sclerosis. In this paper w…