12 citations · 36 across the 7 of their papers we have counts for
8 papers
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…
RMDL: Recalibrated multi-instance deep learning for whole slide gastric image classification
Shujun Wang, Yaxi Zhu, Lequan Yu +5
The whole slide histopathology images (WSIs) play a critical role in gastric cancer diagnosis. However, due to the large scale of WSIs and various sizes of the abnormal area, how t…
Deep Semi-supervised Knowledge Distillation for Overlapping Cervical Cell Instance Segmentation
Yanning Zhou, Hao Chen, Huangjing Lin +1
Deep learning methods show promising results for overlapping cervical cell instance segmentation. However, in order to train a model with good generalization ability, voluminous pi…
Deep Angular Embedding and Feature Correlation Attention for Breast MRI Cancer Analysis
Luyang Luo, Hao Chen, Xi Wang +5
Accurate and automatic analysis of breast MRI plays an important role in early diagnosis and successful treatment planning for breast cancer. Due to the heterogeneity nature, accur…
PFA-ScanNet: Pyramidal Feature Aggregation with Synergistic Learning for Breast Cancer Metastasis Analysis
Zixu Zhao, Huangjing Lin, Hao Chen +1
Automatic detection of cancer metastasis from whole slide images (WSIs) is a crucial step for following patient staging and prognosis. Recent convolutional neural network based app…