19 citations · 23 across the 9 of their papers we have counts for
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cs.CV2019★ 19 cited
Random 2.5D U-net for Fully 3D Segmentation
Christoph Angermann, Markus Haltmeier
Convolutional neural networks are state-of-the-art for various segmentation tasks. While for 2D images these networks are also computationally efficient, 3D convolutions have huge…
cs.CV2019
Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation
Christoph Angermann, Markus Haltmeier, Ruth Steiger +2
Convolutional neural networks are state-of-the-art for various segmentation tasks. While for 2D images these networks are also computationally efficient, 3D convolutions have huge…