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20172020
most citedAn application of cascaded 3D fully convolutional networks for medical image segmentation

332 citations · 513 across the 5 of their papers we have counts for

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5 papers · 1 filter

cs.CV2020★ 26 cited

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…

cs.CV2018★ 9 cited

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…

cs.CV2018★ 332 cited

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…

cs.CV2017★ 27 cited

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…

cs.CV2017★ 119 cited

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…