activity
20172021
most citedDilated FCN for Multi-Agent 2D/3D Medical Image Registration

15 citations · 41 across the 8 of their papers we have counts for

collaborators

15 papers

cs.CV2021

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,…

eess.IV20211 cited

Opportunistic Screening of Osteoporosis Using Plain Film Chest X-ray

Fakai Wang, Kang Zheng, Yirui Wang +6

Osteoporosis is a common chronic metabolic bone disease that is often under-diagnosed and under-treated due to the limited access to bone mineral density (BMD) examinations, Dual-e…

eess.IV2021

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…

cs.CV20217 cited

A New Window Loss Function for Bone Fracture Detection and Localization in X-ray Images with Point-based Annotation

Xinyu Zhang, Yirui Wang, Chi-Tung Cheng +5

Object detection methods are widely adopted for computer-aided diagnosis using medical images. Anomalous findings are usually treated as objects that are described by bounding boxe…

cs.CV20201 cited

Automatic Vertebra Localization and Identification in CT by Spine Rectification and Anatomically-constrained Optimization

Fakai Wang, Kang Zheng, Le Lu +3

Accurate vertebra localization and identification are required in many clinical applications of spine disorder diagnosis and surgery planning. However, significant challenges are p…

cs.CV20204 cited

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…