180 citations · 371 across the 6 of their papers we have counts for
6 papers
Spatial Aggregation of Holistically-Nested Convolutional Neural Networks for Automated Pancreas Localization and Segmentation
Holger R. Roth, Le Lu, Nathan Lay +4
Accurate and automatic organ segmentation from 3D radiological scans is an important yet challenging problem for medical image analysis. Specifically, the pancreas demonstrates ver…
Spatial Aggregation of Holistically-Nested Networks for Automated Pancreas Segmentation
Holger R. Roth, Le Lu, Amal Farag +2
Accurate automatic organ segmentation is an important yet challenging problem for medical image analysis. The pancreas is an abdominal organ with very high anatomical variability.…
DeepOrgan: Multi-level Deep Convolutional Networks for Automated Pancreas Segmentation
Holger R. Roth, Le Lu, Amal Farag +4
Automatic organ segmentation is an important yet challenging problem for medical image analysis. The pancreas is an abdominal organ with very high anatomical variability. This inhi…
A Bottom-up Approach for Pancreas Segmentation using Cascaded Superpixels and (Deep) Image Patch Labeling
Amal Farag, Le Lu, Holger R. Roth +3
Robust automated organ segmentation is a prerequisite for computer-aided diagnosis (CAD), quantitative imaging analysis and surgical assistance. For high-variability organs such as…
Deep convolutional networks for pancreas segmentation in CT imaging
Holger R. Roth, Amal Farag, Le Lu +2
Automatic organ segmentation is an important prerequisite for many computer-aided diagnosis systems. The high anatomical variability of organs in the abdomen, such as the pancreas,…
A Bottom-Up Approach for Automatic Pancreas Segmentation in Abdominal CT Scans
Amal Farag, Le Lu, Evrim Turkbey +2
Organ segmentation is a prerequisite for a computer-aided diagnosis (CAD) system to detect pathologies and perform quantitative analysis. For anatomically high-variability abdomina…