3 citations · 6 across the 3 of their papers we have counts for
5 papers
Multi-phase Liver Tumor Segmentation with Spatial Aggregation and Uncertain Region Inpainting
Yue Zhang, Chengtao Peng, Liying Peng +8
Multi-phase computed tomography (CT) images provide crucial complementary information for accurate liver tumor segmentation (LiTS). State-of-the-art multi-phase LiTS methods usuall…
Automatic CT Segmentation from Bounding Box Annotations using Convolutional Neural Networks
Yuanpeng Liu, Qinglei Hui, Zhiyi Peng +2
Accurate segmentation for medical images is important for clinical diagnosis. Existing automatic segmentation methods are mainly based on fully supervised learning and have an extr…
Graph-based Pyramid Global Context Reasoning with a Saliency-aware Projection for COVID-19 Lung Infections Segmentation
Huimin Huang, Ming Cai, Lanfen Lin +9
Coronavirus Disease 2019 (COVID-19) has rapidly spread in 2020, emerging a mass of studies for lung infection segmentation from CT images. Though many methods have been proposed fo…
PA-ResSeg: A Phase Attention Residual Network for Liver Tumor Segmentation from Multi-phase CT Images
Yingying Xu, Ming Cai, Lanfen Lin +10
In this paper, we propose a phase attention residual network (PA-ResSeg) to model multi-phase features for accurate liver tumor segmentation, in which a phase attention (PA) is new…
Automatic 3D liver location and segmentation via convolutional neural networks and graph cut
Fang Lu, Fa Wu, Peijun Hu +2
Purpose Segmentation of the liver from abdominal computed tomography (CT) image is an essential step in some computer assisted clinical interventions, such as surgery planning for…