129 citations · 306 across the 14 of their papers we have counts for
5 papers · 1 filter
Learning Image Labels On-the-fly for Training Robust Classification Models
Xiaosong Wang, Ziyue Xu, Dong Yang +3
Current deep learning paradigms largely benefit from the tremendous amount of annotated data. However, the quality of the annotations often varies among labelers. Multi-observer st…
Going to Extremes: Weakly Supervised Medical Image Segmentation
Holger R Roth, Dong Yang, Ziyue Xu +2
Medical image annotation is a major hurdle for developing precise and robust machine learning models. Annotation is expensive, time-consuming, and often requires expert knowledge,…
Weakly supervised one-stage vision and language disease detection using large scale pneumonia and pneumothorax studies
Leo K. Tam, Xiaosong Wang, Evrim Turkbey +3
Detecting clinically relevant objects in medical images is a challenge despite large datasets due to the lack of detailed labels. To address the label issue, we utilize the scene-l…
Multi-Domain Image Completion for Random Missing Input Data
Liyue Shen, Wentao Zhu, Xiaosong Wang +9
Multi-domain data are widely leveraged in vision applications taking advantage of complementary information from different modalities, e.g., brain tumor segmentation from multi-par…
When Radiology Report Generation Meets Knowledge Graph
Yixiao Zhang, Xiaosong Wang, Ziyue Xu +3
Automatic radiology report generation has been an attracting research problem towards computer-aided diagnosis to alleviate the workload of doctors in recent years. Deep learning t…