Publications (5)
Contour Transformer Network for One-shot Segmentation of Anatomical Structures
Yuhang Lu, Kang Zheng, Weijian Li +8
Accurate segmentation of anatomical structures is vital for medical image analysis. The state-of-the-art accuracy is typically achieved by supervised learning methods, where gather…
Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images
Kang Zheng, Yirui Wang, Xiaoyun Zhou +8
Bone mineral density (BMD) is a clinically critical indicator of osteoporosis, usually measured by dual-energy X-ray absorptiometry (DEXA). Due to the limited accessibility of DEXA…
Scalable Semi-supervised Landmark Localization for X-ray Images using Few-shot Deep Adaptive Graph
Xiao-Yun Zhou, Bolin Lai, Weijian Li +12
Landmark localization plays an important role in medical image analysis. Learning based methods, including CNN and GCN, have demonstrated the state-of-the-art performance. However,…
Learning to Segment Anatomical Structures Accurately from One Exemplar
Yuhang Lu, Weijian Li, Kang Zheng +8
Accurate segmentation of critical anatomical structures is at the core of medical image analysis. The main bottleneck lies in gathering the requisite expert-labeled image annotatio…
Structured Landmark Detection via Topology-Adapting Deep Graph Learning
Weijian Li, Yuhang Lu, Kang Zheng +8
Image landmark detection aims to automatically identify the locations of predefined fiducial points. Despite recent success in this field, higher-ordered structural modeling to cap…