15 citations · 27 across the 6 of their papers we have counts for
7 papers
Automated Generation of Accurate \& Fluent Medical X-ray Reports
Hoang T. N. Nguyen, Dong Nie, Taivanbat Badamdorj +4
Our paper focuses on automating the generation of medical reports from chest X-ray image inputs, a critical yet time-consuming task for radiologists. Unlike existing medical re-por…
HF-UNet: Learning Hierarchically Inter-Task Relevance in Multi-Task U-Net for Accurate Prostate Segmentation
Kelei He, Chunfeng Lian, Bing Zhang +6
Accurate segmentation of the prostate is a key step in external beam radiation therapy treatments. In this paper, we tackle the challenging task of prostate segmentation in CT imag…
Hybrid Graph Neural Networks for Crowd Counting
Ao Luo, Fan Yang, Xin Li +4
Crowd counting is an important yet challenging task due to the large scale and density variation. Recent investigations have shown that distilling rich relations among multi-scale…
Dual Adversarial Learning with Attention Mechanism for Fine-grained Medical Image Synthesis
Dong Nie, Lei Xiang, Qian Wang +1
Medical imaging plays a critical role in various clinical applications. However, due to multiple considerations such as cost and risk, the acquisition of certain image modalities c…
Task Decomposition and Synchronization for Semantic Biomedical Image Segmentation
Xuhua Ren, Lichi Zhang, Sahar Ahmad +5
Semantic segmentation is essentially important to biomedical image analysis. Many recent works mainly focus on integrating the Fully Convolutional Network (FCN) architecture with s…
Semantic-guided Encoder Feature Learning for Blurry Boundary Delineation
Dong Nie, Dinggang Shen
Encoder-decoder architectures are widely adopted for medical image segmentation tasks. With the lateral skip connection, the models can obtain and fuse both semantic and resolution…