%0 Journal Article %1 journals/mia/SchmitzMNKSWR21 %A Schmitz, Rüdiger %A Madesta, Frederic %A Nielsen, Maximilian %A Krause, Jenny %A Steurer, Stefan %A Werner, René %A Rösch, Thomas %D 2021 %J Medical Image Anal. %K dblp %P 101996 %T Multi-scale fully convolutional neural networks for histopathology image segmentation: From nuclear aberrations to the global tissue architecture. %U http://dblp.uni-trier.de/db/journals/mia/mia70.html#SchmitzMNKSWR21 %V 70

@article{journals/mia/SchmitzMNKSWR21, added-at = {2021-05-14T00:00:00.000+0200}, author = {Schmitz, Rüdiger and Madesta, Frederic and Nielsen, Maximilian and Krause, Jenny and Steurer, Stefan and Werner, René and Rösch, Thomas}, biburl = {https://www.bibsonomy.org/bibtex/214109131bf4b15656158de391bad76d8/dblp}, ee = {https://doi.org/10.1016/j.media.2021.101996}, interhash = {e742dca5e62a8df71d65f568172c2e5a}, intrahash = {14109131bf4b15656158de391bad76d8}, journal = {Medical Image Anal.}, keywords = {dblp}, pages = 101996, timestamp = {2024-04-08T15:55:21.000+0200}, title = {Multi-scale fully convolutional neural networks for histopathology image segmentation: From nuclear aberrations to the global tissue architecture.}, url = {http://dblp.uni-trier.de/db/journals/mia/mia70.html#SchmitzMNKSWR21}, volume = 70, year = 2021 }