26 citations · 26 across the 2 of their papers we have counts for
5 papers · 1 filter
Regression Forest-Based Atlas Localization and Direction Specific Atlas Generation for Pancreas Segmentation
Masahiro Oda, Natsuki Shimizu, Ken'ichi Karasawa +6
This paper proposes a fully automated atlas-based pancreas segmentation method from CT volumes utilizing atlas localization by regression forest and atlas generation using blood ve…
3D FCN Feature Driven Regression Forest-Based Pancreas Localization and Segmentation
Masahiro Oda, Natsuki Shimizu, Holger R. Roth +6
This paper presents a fully automated atlas-based pancreas segmentation method from CT volumes utilizing 3D fully convolutional network (FCN) feature-based pancreas localization. S…
An application of cascaded 3D fully convolutional networks for medical image segmentation
Holger R. Roth, Hirohisa Oda, Xiangrong Zhou +7
Recent advances in 3D fully convolutional networks (FCN) have made it feasible to produce dense voxel-wise predictions of volumetric images. In this work, we show that a multi-clas…
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…
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…