105 citations · 380 across the 28 of their papers we have counts for
13 papers · 1 filter
Motion-to-Matching: A Mixed Paradigm for 3D Single Object Tracking
Zhiheng Li, Yu Lin, Yubo Cui +2
3D single object tracking with LiDAR points is an important task in the computer vision field. Previous methods usually adopt the matching-based or motion-centric paradigms to esti…
Geometric Visual Similarity Learning in 3D Medical Image Self-supervised Pre-training
Yuting He, Guanyu Yang, Rongjun Ge +4
Learning inter-image similarity is crucial for 3D medical images self-supervised pre-training, due to their sharing of numerous same semantic regions. However, the lack of the sema…
Direct Estimation of Spinal Cobb Angles by Structured Multi-Output Regression
Haoliang Sun, Xiantong Zhen, Chris Bailey +3
The Cobb angle that quantitatively evaluates the spinal curvature plays an important role in the scoliosis diagnosis and treatment. Conventional measurement of these angles suffers…
Direct Automated Quantitative Measurement of Spine via Cascade Amplifier Regression Network
Shumao Pang, Stephanie Leung, Ilanit Ben Nachum +2
Automated quantitative measurement of the spine (i.e., multiple indices estimation of heights, widths, areas, and so on for the vertebral body and disc) is of the utmost importance…
Cardiac Motion Scoring with Segment- and Subject-level Non-Local Modeling
Wufeng Xue, Gary Brahm, Stephanie Leung +2
Motion scoring of cardiac myocardium is of paramount importance for early detection and diagnosis of various cardiac disease. It aims at identifying regional wall motions into one…
VoxelAtlasGAN: 3D Left Ventricle Segmentation on Echocardiography with Atlas Guided Generation and Voxel-to-voxel Discrimination
Suyu Dong, Gongning Luo, Kuanquan Wang +5
3D left ventricle (LV) segmentation on echocardiography is very important for diagnosis and treatment of cardiac disease. It is not only because of that echocardiography is a real-…