Spatial feature fusion convolutional network for liver and liver tumor segmentation from CT images

CE-Net: Context Encoder Network for 2D Medical Image Segmentation

(2019) Zaiwang Gu et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Bottleneck feature supervised U-Net for pixel-wise liver and tumor segmentation

(2019) Song LI et al.   EXPERT SYSTEMS WITH APPLICATIONS

An application of cascaded 3D fully convolutional networks for medical image segmentation

(2018) Holger R. Roth et al.   COMPUTERIZED MEDICAL IMAGING AND GRAPHICS

H-DenseUNet: Hybrid Densely Connected UNet for Liver and Tumor Segmentation from CT Volumes

(2018) Xiaomeng Li et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Fully Convolutional Networks for Semantic Segmentation

(2017) Evan Shelhamer et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Automatic Liver Segmentation on Volumetric CT Images Using Supervoxel-Based Graph Cuts

(2016) Weiwei Wu et al.   Computational and Mathematical Methods in Medicine

Scale-adaptive supervoxel-based random forests for liver tumor segmentation in dynamic contrast-enhanced CT scans

(2016) Pierre-Henri Conze et al.   International Journal of Computer Assisted Radiology and Surgery

A conditional statistical shape model with integrated error estimation of the conditions; Application to liver segmentation in non-contrast CT images

(2013) Sho Tomoshige et al.   MEDICAL IMAGE ANALYSIS

Hepatocellular carcinoma

(2012) Alejandro Forner et al.   LANCET

Automatic Liver Segmentation Using a Statistical Shape Model With Optimal Surface Detection

(2010) Xing Zhang et al.   IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING