69 citations · 75 across the 7 of their papers we have counts for
7 papers
Tailored Multi-Organ Segmentation with Model Adaptation and Ensemble
Jiahua Dong, Guohua Cheng, Yue Zhang +5
Multi-organ segmentation, which identifies and separates different organs in medical images, is a fundamental task in medical image analysis. Recently, the immense success of deep…
Automatic hippocampal surface generation via 3D U-net and active shape modeling with hybrid particle swarm optimization
Pinyuan Zhong, Yue Zhang, Xiaoying Tang
In this paper, we proposed and validated a fully automatic pipeline for hippocampal surface generation via 3D U-net coupled with active shape modeling (ASM). Principally, the propo…
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…
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…
Coarse-to-fine Kidney Segmentation Framework Incorporating with Abnormal Detection and Correction
Yue Zhang, Jiong Wu, Yu Zhou +2
In this paper, we formulated the kidney segmentation task in a coarse-to-fine fashion, predicting a coarse label based on the entire CT image and a fine label based on the coarse s…
Prostate segmentation using Z-net
Yue Zhang, Jiong Wu, Wanli Chen +2
In this paper, we proposed a novel architecture of convolutional neural network (CNN), namely Z-net, for segmenting prostate from magnetic resonance images (MRIs). In the proposed…
Prostate Segmentation using 2D Bridged U-net
Wanli Chen, Yue Zhang, Junjun He +4
In this paper, we focus on three problems in deep learning based medical image segmentation. Firstly, U-net, as a popular model for medical image segmentation, is difficult to trai…