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Towards dense volumetric pancreas segmentation in CT using 3D fully convolutional networks
Holger Roth, Masahiro Oda, Natsuki Shimizu +6
Pancreas segmentation in computed tomography imaging has been historically difficult for automated methods because of the large shape and size variations between patients. In this…
Employing Weak Annotations for Medical Image Analysis Problems
Martin Rajchl, Lisa M. Koch, Christian Ledig +4
To efficiently establish training databases for machine learning methods, collaborative and crowdsourcing platforms have been investigated to collectively tackle the annotation eff…
Hierarchical 3D fully convolutional networks for multi-organ segmentation
Holger R. Roth, Hirohisa Oda, Yuichiro Hayashi +5
Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of full volumetric images. In this work, we show that a multi…