59 citations · 92 across the 18 of their papers we have counts for
5 papers · 1 filter
Adversarial Medical Image with Hierarchical Feature Hiding
Qingsong Yao, Zecheng He, Yuexiang Li +4
Deep learning based methods for medical images can be easily compromised by adversarial examples (AEs), posing a great security flaw in clinical decision-making. It has been discov…
Rib Suppression in Digital Chest Tomosynthesis
Yihua Sun, Qingsong Yao, Yuanyuan Lyu +4
Digital chest tomosynthesis (DCT) is a technique to produce sectional 3D images of a human chest for pulmonary disease screening, with 2D X-ray projections taken within an extremel…
Which images to label for few-shot medical landmark detection?
Quan Quan, Qingsong Yao, Jun Li +1
The success of deep learning methods relies on the availability of well-labeled large-scale datasets. However, for medical images, annotating such abundant training data often requ…
Label-Free Segmentation of COVID-19 Lesions in Lung CT
Qingsong Yao, Li Xiao, Peihang Liu +1
Scarcity of annotated images hampers the building of automated solution for reliable COVID-19 diagnosis and evaluation from CT. To alleviate the burden of data annotation, we herei…
3D U-Net: A 3D Universal U-Net for Multi-Domain Medical Image Segmentation
Chao Huang, Hu Han, Qingsong Yao +2
Fully convolutional neural networks like U-Net have been the state-of-the-art methods in medical image segmentation. Practically, a network is highly specialized and trained separa…