19 citations · 22 across the 4 of their papers we have counts for
4 papers
Unleashing the Strengths of Unlabeled Data in Pan-cancer Abdominal Organ Quantification: the FLARE22 Challenge
Jun Ma, Yao Zhang, Song Gu +26
Quantitative organ assessment is an essential step in automated abdominal disease diagnosis and treatment planning. Artificial intelligence (AI) has shown great potential to automa…
Multi-Target Landmark Detection with Incomplete Images via Reinforcement Learning and Shape Prior
Kaiwen Wan, Lei Li, Dengqiang Jia +9
Medical images are generally acquired with limited field-of-view (FOV), which could lead to incomplete regions of interest (ROI), and thus impose a great challenge on medical image…
A low-rank representation for unsupervised registration of medical images
Dengqiang Jia, Shangqi Gao, Qunlong Chen +2
Registration networks have shown great application potentials in medical image analysis. However, supervised training methods have a great demand for large and high-quality labeled…
Learning-Based Algorithms for Vessel Tracking: A Review
Dengqiang Jia, Xiahai Zhuang
Developing efficient vessel-tracking algorithms is crucial for imaging-based diagnosis and treatment of vascular diseases. Vessel tracking aims to solve recognition problems such a…