286 citations · 384 across the 34 of their papers we have counts for
4 papers · 1 filter
Rethinking Annotation Granularity for Overcoming Shortcuts in Deep Learning-based Radiograph Diagnosis: A Multicenter Study
Luyang Luo, Hao Chen, Yongjie Xiao +10
Two DL models were developed using radiograph-level annotations (yes or no disease) and fine-grained lesion-level annotations (lesion bounding boxes), respectively named CheXNet an…
Deep Semi-supervised Metric Learning with Dual Alignment for Cervical Cancer Cell Detection
Zhizhong Chai, Luyang Luo, Huangjing Lin +3
Deep learning has achieved unprecedented success in various object detection tasks with huge amounts of labeled data. However, obtaining large-scale annotations for medical images…
Dual-Consistency Semi-Supervised Learning with Uncertainty Quantification for COVID-19 Lesion Segmentation from CT Images
Yanwen Li, Luyang Luo, Huangjing Lin +2
The novel coronavirus disease 2019 (COVID-19) characterized by atypical pneumonia has caused millions of deaths worldwide. Automatically segmenting lesions from chest Computed Tomo…
OXnet: Omni-supervised Thoracic Disease Detection from Chest X-rays
Luyang Luo, Hao Chen, Yanning Zhou +2
Chest X-ray (CXR) is the most typical diagnostic X-ray examination for screening various thoracic diseases. Automatically localizing lesions from CXR is promising for alleviating r…