215 citations · 345 across the 14 of their papers we have counts for
6 papers · 1 filter
Radiology Report Generation with a Learned Knowledge Base and Multi-modal Alignment
Shuxin Yang, Xian Wu, Shen Ge +2
In clinics, a radiology report is crucial for guiding a patient's treatment. However, writing radiology reports is a heavy burden for radiologists. To this end, we present an autom…
Knowledge Matters: Radiology Report Generation with General and Specific Knowledge
Shuxin Yang, Xian Wu, Shen Ge +2
Automatic radiology report generation is critical in clinics which can relieve experienced radiologists from the heavy workload and remind inexperienced radiologists of misdiagnosi…
Pathological Image Segmentation with Noisy Labels
Li Xiao, Yinhao Li, Luxi Qv +3
Segmentation of pathological images is essential for accurate disease diagnosis. The quality of manual labels plays a critical role in segmentation accuracy; yet, in practice, the…
One-Shot Medical Landmark Detection
Qingsong Yao, Quan Quan, Li Xiao +1
The success of deep learning methods relies on the availability of a large number of datasets with annotations; however, curating such datasets is burdensome, especially for medica…
Incremental Learning for Multi-organ Segmentation with Partially Labeled Datasets
Pengbo Liu, Li Xiao, S. Kevin Zhou
There exists a large number of datasets for organ segmentation, which are partially annotated, and sequentially constructed. A typical dataset is constructed at a certain time by c…
You Only Learn Once: Universal Anatomical Landmark Detection
Heqin Zhu, Qingsong Yao, Li Xiao +1
Detecting anatomical landmarks in medical images plays an essential role in understanding the anatomy and planning automated processing. In recent years, a variety of deep neural n…