6 citations · 8 across the 4 of their papers we have counts for
4 papers
Re-thinking and Re-labeling LIDC-IDRI for Robust Pulmonary Cancer Prediction
Hanxiao Zhang, Xiao Gu, Minghui Zhang +6
The LIDC-IDRI database is the most popular benchmark for lung cancer prediction. However, with subjective assessment from radiologists, nodules in LIDC may have entirely different…
Faithful learning with sure data for lung nodule diagnosis
Hanxiao Zhang, Liang Chen, Xiao Gu +6
Recent evolution in deep learning has proven its value for CT-based lung nodule classification. Most current techniques are intrinsically black-box systems, suffering from two gene…
Relationship between pulmonary nodule malignancy and surrounding pleurae, airways and vessels: a quantitative study using the public LIDC-IDRI dataset
Yulei Qin, Yun Gu, Hanxiao Zhang +5
To investigate whether the pleurae, airways and vessels surrounding a nodule on non-contrast computed tomography (CT) can discriminate benign and malignant pulmonary nodules. The L…
Learning Tubule-Sensitive CNNs for Pulmonary Airway and Artery-Vein Segmentation in CT
Yulei Qin, Hao Zheng, Yun Gu +6
Training convolutional neural networks (CNNs) for segmentation of pulmonary airway, artery, and vein is challenging due to sparse supervisory signals caused by the severe class imb…