390 citations · 1.2k across the 17 of their papers we have counts for
5 papers · 1 filter
Dual-Stream Pyramid Registration Network
Miao Kang, Xiaojun Hu, Weilin Huang +2
We propose a Dual-Stream Pyramid Registration Network (referred as Dual-PRNet) for unsupervised 3D medical image registration. Unlike recent CNN-based registration approaches, such…
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…
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…
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…
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…