5 citations · 17 across the 7 of their papers we have counts for
6 papers · 1 filter
MNet: Rethinking 2D/3D Networks for Anisotropic Medical Image Segmentation
Zhangfu Dong, Yuting He, Xiaoming Qi +5
The nature of thick-slice scanning causes severe inter-slice discontinuities of 3D medical images, and the vanilla 2D/3D convolutional neural networks (CNNs) fail to represent spar…
United adversarial learning for liver tumor segmentation and detection of multi-modality non-contrast MRI
Jianfeng Zhao, Dengwang Li, Shuo Li
Simultaneous segmentation and detection of liver tumors (hemangioma and hepatocellular carcinoma (HCC)) by using multi-modality non-contrast magnetic resonance imaging (NCMRI) are…
CPNet: Cycle Prototype Network for Weakly-supervised 3D Renal Compartments Segmentation on CT Images
Song Wang, Yuting He, Youyong Kong +7
Renal compartment segmentation on CT images targets on extracting the 3D structure of renal compartments from abdominal CTA images and is of great significance to the diagnosis and…
EnMcGAN: Adversarial Ensemble Learning for 3D Complete Renal Structures Segmentation
Yuting He, Rongjun Ge, Xiaoming Qi +6
3D complete renal structures(CRS) segmentation targets on segmenting the kidneys, tumors, renal arteries and veins in one inference. Once successful, it will provide preoperative p…
Recurrent Aggregation Learning for Multi-View Echocardiographic Sequences Segmentation
Ming Li, Weiwei Zhang, Guang Yang +5
Multi-view echocardiographic sequences segmentation is crucial for clinical diagnosis. However, this task is challenging due to limited labeled data, huge noise, and large gaps acr…
Direct Quantification for Coronary Artery Stenosis Using Multiview Learning
Dong Zhang, Guang Yang, Shu Zhao +3
The quantification of the coronary artery stenosis is of significant clinical importance in coronary artery disease diagnosis and intervention treatment. It aims to quantify the mo…