193 citations · 246 across the 10 of their papers we have counts for
7 papers · 1 filter
Coordinated Transformer with Position \& Sample-aware Central Loss for Anatomical Landmark Detection
Qikui Zhu, Yihui Bi, Danxin Wang +3
Heatmap-based anatomical landmark detection is still facing two unresolved challenges: 1) inability to accurately evaluate the distribution of heatmap; 2) inability to effectively…
Neural Annotation Refinement: Development of a New 3D Dataset for Adrenal Gland Analysis
Jiancheng Yang, Rui Shi, Udaranga Wickramasinghe +3
The human annotations are imperfect, especially when produced by junior practitioners. Multi-expert consensus is usually regarded as golden standard, while this annotation protocol…
Self-supervised Training of Graph Convolutional Networks
Qikui Zhu, Bo Du, Pingkun Yan
Graph Convolutional Networks (GCNs) have been successfully applied to analyze non-grid data, where the classical convolutional neural networks (CNNs) cannot be directly used. One s…
OASIS: One-pass aligned Atlas Set for Image Segmentation
Qikui Zhu, Bo Du, Pingkun Yan
Medical image segmentation is a fundamental task in medical image analysis. Despite that deep convolutional neural networks have gained stellar performance in this challenging task…
Multi-hop Convolutions on Weighted Graphs
Qikui Zhu, Bo Du, Pingkun Yan
Graph Convolutional Networks (GCNs) have made significant advances in semi-supervised learning, especially for classification tasks. However, existing GCN based methods have two ma…
Boundary-weighted Domain Adaptive Neural Network for Prostate MR Image Segmentation
Qikui Zhu, Bo Du, Pingkun Yan
Accurate segmentation of the prostate from magnetic resonance (MR) images provides useful information for prostate cancer diagnosis and treatment. However, automated prostate segme…
Deeply-Supervised CNN for Prostate Segmentation
Qikui Zhu, Bo Du, Baris Turkbey +2
Prostate segmentation from Magnetic Resonance (MR) images plays an important role in image guided interven- tion. However, the lack of clear boundary specifically at the apex and b…